* installing *source* package 'blavaan' ...
** this is package 'blavaan' version '0.5-8'
** package 'blavaan' successfully unpacked and MD5 sums checked
** using staged installation
** libs
using C++ compiler: 'g++.exe (GCC) 14.2.0'
using C++17
make[1]: Entering directory '/d/temp/2025_07_01_01_50_01_1069/RtmpCWsvVz/R.INSTALL416c733c1086/blavaan/src'
g++ -std=gnu++17 -I"D:/RCompile/recent/R/include" -DNDEBUG -I"../inst/include" -I"D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DRCPP_PARALLEL_USE_TBB=1 -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include' -I'D:/RCompile/CRANpkg/lib/4.6/rstan/include' -I'D:/RCompile/CRANpkg/lib/4.6/BH/include' -I'D:/RCompile/CRANpkg/lib/4.6/Rcpp/include' -I'D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include' -I'D:/RCompile/CRANpkg/lib/4.6/RcppParallel/include' -I"d:/rtools45/x86_64-w64-mingw32.static.posix/include" -DRCPP_PARALLEL_USE_TBB=1 -I"D:/RCompile/CRANpkg/lib/4.6/RcppParallel/include" -D_REENTRANT -DSTAN_THREADS -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c RcppExports.cpp -o RcppExports.o
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:205,
from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Dense:1,
from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/RcppEigenForward.h:28,
from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/RcppEigen.h:25,
from RcppExports.cpp:4:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:46:40: warning: ignoring attributes on template argument '__m128i' [-Wignored-attributes]
46 | typedef eigen_packet_wrapper<__m128i, 0> Packet4i;
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:47:40: warning: ignoring attributes on template argument '__m128i' [-Wignored-attributes]
47 | typedef eigen_packet_wrapper<__m128i, 1> Packet16b;
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:49:39: warning: ignoring attributes on template argument '__m128' [-Wignored-attributes]
49 | template<> struct is_arithmetic<__m128> { enum { value = true }; };
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:50:40: warning: ignoring attributes on template argument '__m128i' [-Wignored-attributes]
50 | template<> struct is_arithmetic<__m128i> { enum { value = true }; };
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:51:40: warning: ignoring attributes on template argument '__m128d' [-Wignored-attributes]
51 | template<> struct is_arithmetic<__m128d> { enum { value = true }; };
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:222:43: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
222 | template<> struct unpacket_traits<Packet4f> {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:228:43: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
228 | template<> struct unpacket_traits<Packet2d> {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1124:34: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
1124 | ptranspose(PacketBlock<Packet4f,4>& kernel) {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1129:34: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
1129 | ptranspose(PacketBlock<Packet2d,2>& kernel) {
| ^
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:174:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
16 | struct conj_helper<PACKET_REAL, PACKET_CPLX, false, false> { \
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro 'EIGEN_MAKE_CONJ_HELPER_CPLX_REAL'
173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f)
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
29 | struct conj_helper<PACKET_CPLX, PACKET_REAL, false, false> { \
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro 'EIGEN_MAKE_CONJ_HELPER_CPLX_REAL'
173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f)
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
16 | struct conj_helper<PACKET_REAL, PACKET_CPLX, false, false> { \
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro 'EIGEN_MAKE_CONJ_HELPER_CPLX_REAL'
298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d)
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
29 | struct conj_helper<PACKET_CPLX, PACKET_REAL, false, false> { \
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro 'EIGEN_MAKE_CONJ_HELPER_CPLX_REAL'
298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d)
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:165:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<float, 4>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<float, 4, 1> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from 'struct Eigen::internal::traits<Eigen::Quaternion<float> >'
266 | Alignment = internal::traits<Coefficients>::Alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here
24 | ResAlignment = traits<Quaternion<float> >::Alignment
| ^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(4) float>::half' {aka '__m128'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:271:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<float, 4, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<float, 4, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<float, 4, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<float, 4, 1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from 'class Eigen::QuaternionBase<Eigen::Quaternion<float> >'
46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType;
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from 'class Eigen::Quaternion<float>'
273 | class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here
27 | {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, 4>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<double, 4, 1> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from 'struct Eigen::internal::traits<Eigen::Quaternion<double> >'
266 | Alignment = internal::traits<Coefficients>::Alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here
98 | ResAlignment = traits<Quaternion<double> >::Alignment
| ^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 4, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 4, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, 4, 1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from 'class Eigen::QuaternionBase<Eigen::Quaternion<double> >'
46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType;
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from 'class Eigen::Quaternion<double>'
273 | class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here
102 | {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/SparseCore:37,
from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Sparse:26,
from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/RcppEigenForward.h:29:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of 'class Eigen::SparseMatrixBase<Eigen::SparseMatrix<double, 0, int> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from 'class Eigen::SparseCompressedBase<Eigen::SparseMatrix<double, 0, int> >'
36 | class SparseCompressedBase
| ^~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from 'class Eigen::SparseMatrix<double, 0, int>'
96 | class SparseMatrix
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here
61 | typedef Triplet<double> T;
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
47 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
g++ -std=gnu++17 -I"D:/RCompile/recent/R/include" -DNDEBUG -I"../inst/include" -I"D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DRCPP_PARALLEL_USE_TBB=1 -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include' -I'D:/RCompile/CRANpkg/lib/4.6/rstan/include' -I'D:/RCompile/CRANpkg/lib/4.6/BH/include' -I'D:/RCompile/CRANpkg/lib/4.6/Rcpp/include' -I'D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include' -I'D:/RCompile/CRANpkg/lib/4.6/RcppParallel/include' -I"d:/rtools45/x86_64-w64-mingw32.static.posix/include" -DRCPP_PARALLEL_USE_TBB=1 -I"D:/RCompile/CRANpkg/lib/4.6/RcppParallel/include" -D_REENTRANT -DSTAN_THREADS -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c stanExports_stanmarg.cc -o stanExports_stanmarg.o
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:205,
from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Dense:1,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:22,
from D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/rstaninc.hpp:3,
from stanExports_stanmarg.h:23,
from stanExports_stanmarg.cc:5:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:46:40: warning: ignoring attributes on template argument '__m128i' [-Wignored-attributes]
46 | typedef eigen_packet_wrapper<__m128i, 0> Packet4i;
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:47:40: warning: ignoring attributes on template argument '__m128i' [-Wignored-attributes]
47 | typedef eigen_packet_wrapper<__m128i, 1> Packet16b;
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:49:39: warning: ignoring attributes on template argument '__m128' [-Wignored-attributes]
49 | template<> struct is_arithmetic<__m128> { enum { value = true }; };
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:50:40: warning: ignoring attributes on template argument '__m128i' [-Wignored-attributes]
50 | template<> struct is_arithmetic<__m128i> { enum { value = true }; };
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:51:40: warning: ignoring attributes on template argument '__m128d' [-Wignored-attributes]
51 | template<> struct is_arithmetic<__m128d> { enum { value = true }; };
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:222:43: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
222 | template<> struct unpacket_traits<Packet4f> {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:228:43: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
228 | template<> struct unpacket_traits<Packet2d> {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1124:34: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
1124 | ptranspose(PacketBlock<Packet4f,4>& kernel) {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1129:34: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
1129 | ptranspose(PacketBlock<Packet2d,2>& kernel) {
| ^
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:174:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
16 | struct conj_helper<PACKET_REAL, PACKET_CPLX, false, false> { \
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro 'EIGEN_MAKE_CONJ_HELPER_CPLX_REAL'
173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f)
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
29 | struct conj_helper<PACKET_CPLX, PACKET_REAL, false, false> { \
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro 'EIGEN_MAKE_CONJ_HELPER_CPLX_REAL'
173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f)
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
16 | struct conj_helper<PACKET_REAL, PACKET_CPLX, false, false> { \
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro 'EIGEN_MAKE_CONJ_HELPER_CPLX_REAL'
298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d)
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
29 | struct conj_helper<PACKET_CPLX, PACKET_REAL, false, false> { \
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro 'EIGEN_MAKE_CONJ_HELPER_CPLX_REAL'
298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d)
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:165:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<float, 4>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<float, 4, 1> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from 'struct Eigen::internal::traits<Eigen::Quaternion<float> >'
266 | Alignment = internal::traits<Coefficients>::Alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here
24 | ResAlignment = traits<Quaternion<float> >::Alignment
| ^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(4) float>::half' {aka '__m128'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:271:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<float, 4, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<float, 4, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<float, 4, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<float, 4, 1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from 'class Eigen::QuaternionBase<Eigen::Quaternion<float> >'
46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType;
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from 'class Eigen::Quaternion<float>'
273 | class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here
27 | {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type' {aka '__m128'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, 4>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<double, 4, 1> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from 'struct Eigen::internal::traits<Eigen::Quaternion<double> >'
266 | Alignment = internal::traits<Coefficients>::Alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here
98 | ResAlignment = traits<Quaternion<double> >::Alignment
| ^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 4, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 4, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, 4, 1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from 'class Eigen::QuaternionBase<Eigen::Quaternion<double> >'
46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType;
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from 'class Eigen::Quaternion<double>'
273 | class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here
102 | {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/smart_ptr/shared_ptr.hpp:17,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/shared_ptr.hpp:17,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/date_time/time_clock.hpp:17,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/date_time/posix_time/posix_time_types.hpp:10,
from D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:15,
from D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/rstaninc.hpp:4:
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/smart_ptr/detail/shared_count.hpp:326:33: warning: 'template<class> class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
326 | explicit shared_count( std::auto_ptr<Y> & r ): pi_( new sp_counted_impl_p<Y>( r.get() ) )
| ^~~~~~~~
In file included from D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/memory:78,
from D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:7:
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/unique_ptr.h:59:28: note: declared here
59 | template<typename> class auto_ptr;
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/smart_ptr/shared_ptr.hpp:354:31: warning: 'template<class> class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
354 | explicit shared_ptr( std::auto_ptr<Y> & r ): px(r.get()), pn()
| ^~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/unique_ptr.h:59:28: note: declared here
59 | template<typename> class auto_ptr;
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/smart_ptr/shared_ptr.hpp:365:22: warning: 'template<class> class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
365 | shared_ptr( std::auto_ptr<Y> && r ): px(r.get()), pn()
| ^~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/unique_ptr.h:59:28: note: declared here
59 | template<typename> class auto_ptr;
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/smart_ptr/shared_ptr.hpp:423:34: warning: 'template<class> class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
423 | shared_ptr & operator=( std::auto_ptr<Y> & r )
| ^~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/unique_ptr.h:59:28: note: declared here
59 | template<typename> class auto_ptr;
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/smart_ptr/shared_ptr.hpp:430:34: warning: 'template<class> class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
430 | shared_ptr & operator=( std::auto_ptr<Y> && r )
| ^~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/unique_ptr.h:59:28: note: declared here
59 | template<typename> class auto_ptr;
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/smart_ptr/shared_ptr.hpp: In member function 'boost::shared_ptr<T>& boost::shared_ptr<T>::operator=(std::auto_ptr<_Up>&&)':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/smart_ptr/shared_ptr.hpp:432:38: warning: 'template<class> class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
432 | this_type( static_cast< std::auto_ptr<Y> && >( r ) ).swap( *this );
| ^~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/unique_ptr.h:59:28: note: declared here
59 | template<typename> class auto_ptr;
| ^~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/SparseCore:37,
from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Sparse:26,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:23:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of 'class Eigen::SparseMatrixBase<Eigen::SparseMatrix<double, 0, int> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from 'class Eigen::SparseCompressedBase<Eigen::SparseMatrix<double, 0, int> >'
36 | class SparseCompressedBase
| ^~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from 'class Eigen::SparseMatrix<double, 0, int>'
96 | class SparseMatrix
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here
61 | typedef Triplet<double> T;
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
47 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, -1>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<double, -1, -1> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:19:52: required from 'struct Eigen::internal::traits<Eigen::LDLT<Eigen::Matrix<double, -1, -1> > >'
19 | template<typename _MatrixType, int _UpLo> struct traits<LDLT<_MatrixType, _UpLo> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from 'struct Eigen::EigenBase<Eigen::LDLT<Eigen::Matrix<double, -1, -1> > >'
42 | typedef typename internal::traits<Derived>::StorageKind StorageKind;
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolverBase.h:68:7: required from 'class Eigen::SolverBase<Eigen::LDLT<Eigen::Matrix<double, -1, -1> > >'
68 | class SolverBase : public EigenBase<Derived>
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:59:49: required from 'class Eigen::LDLT<Eigen::Matrix<double, -1, -1> >'
59 | template<typename _MatrixType, int _UpLo> class LDLT
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here
46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive()
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, -1, -1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, -1, -1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, -1, -1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:69:42: required from 'class Eigen::LDLT<Eigen::Matrix<double, -1, -1> >'
69 | MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
| ^~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here
46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive()
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, -1, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, -1, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, -1, 1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:287:19: required from 'class Eigen::LDLT<Eigen::Matrix<double, -1, -1> >'
287 | TmpMatrixType m_temporary;
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here
46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive()
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:29: required from here
47 | || (cholesky.vectorD().array() <= 0.0).any()) {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:41: required from here
47 | || (cholesky.vectorD().array() <= 0.0).any()) {
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_LE>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_LE>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_LE>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:45: required from here
47 | || (cholesky.vectorD().array() <= 0.0).any()) {
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Matrix<double, -1, -1>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Matrix<double, -1, -1>, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:26: required from here
35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1>'
56 | template<typename VectorType, int Size> class VectorBlock
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:34: required from here
35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/linspaced_array.hpp:37:49: required from here
37 | Eigen::VectorXd v = Eigen::VectorXd::LinSpaced(K, low, high);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, -1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, -1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, -1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 1, -1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 1, -1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 1, -1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, 1, -1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:28: required from here
32 | return Eigen::RowVectorXd::LinSpaced(K, low, high);
| ^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, 1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, 1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, 1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, 1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:39: required from here
32 | return Eigen::RowVectorXd::LinSpaced(K, low, high);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Array<double, -1, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Array<double, -1, 1> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Array<double, -1, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from 'class Eigen::Array<double, -1, 1>'
45 | class Array
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:53: required from here
58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2));
| ^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:72: required from here
58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2));
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:77: required from here
58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2));
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:17: required from here
71 | A.diagonal().array() -= mu;
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:29: required from here
71 | A.diagonal().array() -= mu;
| ^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here
86 | bi = (t / (s * (j + 1))) * (A * bi);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here
86 | bi = (t / (s * (j + 1))) * (A * bi);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here
86 | bi = (t / (s * (j + 1))) * (A * bi);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:22: required from here
106 | return x.cwiseAbs().rowwise().sum().maxCoeff();
| ~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from 'class Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>'
56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type,
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:38: required from here
106 | return x.cwiseAbs().rowwise().sum().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:178:58: required from here
178 | alpha = Eigen::VectorXd::Constant(_p_max - 1, normA);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:44: required from 'stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)> [with auto:244 = Eigen::Matrix<double, -1, -1>]'
57 | x, [](const auto& v) { return v.array().ceil(); });
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>]'
47 | f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from 'auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix<double, -1, -1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0; stan::require_not_var_matrix_t<Container>* <anonymous> = 0]'
56 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
57 | x, [](const auto& v) { return v.array().ceil(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here
197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal();
| ~~~~~~~~~~~~~~~~^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:51: required from 'stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)> [with auto:244 = Eigen::Matrix<double, -1, -1>]'
57 | x, [](const auto& v) { return v.array().ceil(); });
| ~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>]'
47 | f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from 'auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix<double, -1, -1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0; stan::require_not_var_matrix_t<Container>* <anonymous> = 0]'
56 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
57 | x, [](const auto& v) { return v.array().ceil(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here
197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal();
| ~~~~~~~~~~~~~~~~^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary<Eigen::Matrix<double, -1, -1>, void>::apply<stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)> >(const Eigen::Matrix<double, -1, -1>&, const stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>&)::<lambda(const auto:6&)> [with auto:6 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary<Eigen::Matrix<double, -1, -1>, void>::apply<stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)> >(const Eigen::Matrix<double, -1, -1>&, const stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>&)::<lambda(const auto:6&)>; Args = {Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1, 0, -1, -1> > >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
47 | f(x));
| ~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from 'auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix<double, -1, -1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0; stan::require_not_var_matrix_t<Container>* <anonymous> = 0]'
56 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
57 | x, [](const auto& v) { return v.array().ceil(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here
197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal();
| ~~~~~~~~~~~~~~~~^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::PartialReduxExpr<Eigen::Matrix<double, -1, -1>, Eigen::internal::member_minCoeff<double, double>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::PartialReduxExpr<Eigen::Matrix<double, -1, -1>, Eigen::internal::member_minCoeff<double, double>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::PartialReduxExpr<Eigen::Matrix<double, -1, -1>, Eigen::internal::member_minCoeff<double, double>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from 'class Eigen::PartialReduxExpr<Eigen::Matrix<double, -1, -1>, Eigen::internal::member_minCoeff<double, double>, 0>'
56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type,
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:203:38: required from here
203 | int cost = c.colwise().minCoeff().minCoeff(&m);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/one_hot_row_vector.hpp:25:52: required from here
25 | Eigen::RowVectorXd ret = Eigen::RowVectorXd::Zero(K);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:13:64: required from here
13 | : m_(Eigen::VectorXd::Zero(n)), m2_(Eigen::MatrixXd::Zero(n, n)) {
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:26:31: required from here
26 | Eigen::VectorXd delta(q - m_);
| ^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here
27 | m_ += delta / num_samples_;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here
27 | m_ += delta / num_samples_;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<Eigen::Matrix<double, -1, 1> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:38: required from here
28 | m2_ += (q - m_) * delta.transpose();
| ~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here
28 | m2_ += (q - m_) * delta.transpose();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:37:40: required from here
37 | covar = m2_ / (num_samples_ - 1.0);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_var_estimator.hpp:28:30: required from here
28 | m2_ += delta.cwiseProduct(q - m_);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/coupled_ode_system.hpp:77:63: required from here
77 | Eigen::Map<Eigen::VectorXd>(dz_dt.data(), dz_dt.size()) = f_y_t;
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor.hpp:13,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim.hpp:15,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/dump.hpp:7,
from D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:43:
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function 'void stan::math::internal::combination(std::vector<int>&, const int&, const int&, const int&)':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:73:29: warning: comparison of integer expressions of different signedness: 'std::size_t' {aka 'long long unsigned int'} and 'int' [-Wsign-compare]
73 | for (std::size_t i = 0; i < p - 1; i++) {
| ~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:79:16: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'const int' [-Wsign-compare]
79 | } while (k < x);
| ~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function 'void stan::math::internal::combos(const int&, const double&, const int&, std::vector<std::vector<double> >&)':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:102:29: warning: comparison of integer expressions of different signedness: 'std::size_t' {aka 'long long unsigned int'} and 'int' [-Wsign-compare]
102 | for (std::size_t i = 1; i != choose_dimk + 1; i++) {
| ~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:105:31: warning: comparison of integer expressions of different signedness: 'std::size_t' {aka 'long long unsigned int'} and 'const int' [-Wsign-compare]
105 | for (std::size_t j = 0; j != k; j++) {
| ~~^~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function 'void stan::math::internal::increment(std::vector<bool>&, const int&, const double&, const std::vector<int>&, std::vector<double>&)':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:126:31: warning: comparison of integer expressions of different signedness: 'std::size_t' {aka 'long long unsigned int'} and 'const int' [-Wsign-compare]
126 | for (std::size_t j = 0; j != k; j++) {
| ~~^~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:132:22: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<bool>::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
132 | while ((first_zero < index.size()) && index[first_zero]) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:135:18: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<bool>::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
135 | if (first_zero == index.size()) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:143:31: warning: comparison of integer expressions of different signedness: 'std::size_t' {aka 'long long unsigned int'} and 'int' [-Wsign-compare]
143 | for (std::size_t i = 0; i != first_zero + 1; i++) {
| ~~^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function 'void stan::math::internal::signcombos(const int&, const double&, const int&, std::vector<std::vector<double> >&)':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:168:29: warning: comparison of integer expressions of different signedness: 'std::size_t' {aka 'long long unsigned int'} and 'int' [-Wsign-compare]
168 | for (std::size_t i = 1; i != choose_dimk + 1; i++) {
| ~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/ode_store_sensitivities.hpp:40:64: required from here
40 | coupled_state.size());
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/aux_/na_assert.hpp:23,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/arg.hpp:25,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/placeholders.hpp:24,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/apply.hpp:24,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/serialization/array_optimization.hpp:18,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/serialization/array_wrapper.hpp:21,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/serialization/array.hpp:26,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/numeric/ublas/storage.hpp:22,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/numeric/ublas/vector.hpp:21,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:23,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/numeric/odeint.hpp:25,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/ode_rk45.hpp:9,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/integrate_ode_rk45.hpp:6,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor.hpp:16:
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/assert.hpp: At global scope:
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/assert.hpp:194:21: warning: unnecessary parentheses in declaration of 'assert_arg' [-Wparentheses]
194 | failed ************ (Pred::************
| ^~~~~~~~~~~~~~~~~~~
195 | assert_arg( void (*)(Pred), typename assert_arg_pred<Pred>::type )
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
196 | );
| ~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/assert.hpp:194:21: note: remove parentheses
194 | failed ************ (Pred::************
| ^~~~~~~~~~~~~~~~~~~
| -
195 | assert_arg( void (*)(Pred), typename assert_arg_pred<Pred>::type )
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
196 | );
| ~
| -
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/assert.hpp:199:21: warning: unnecessary parentheses in declaration of 'assert_not_arg' [-Wparentheses]
199 | failed ************ (boost::mpl::not_<Pred>::************
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not<Pred>::type )
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
201 | );
| ~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/mpl/assert.hpp:199:21: note: remove parentheses
199 | failed ************ (boost::mpl::not_<Pred>::************
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
| -
200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not<Pred>::type )
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
201 | );
| ~
| -
In file included from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/fusion/functional/invocation/detail/that_ptr.hpp:13,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/fusion/functional/invocation/invoke.hpp:52,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/fusion/functional/adapter/fused.hpp:17,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/fusion/functional/generation/make_fused.hpp:13,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/fusion/include/make_fused.hpp:11,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/numeric/odeint/util/resize.hpp:30,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/numeric/odeint/util/state_wrapper.hpp:26,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:33:
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/get_pointer.hpp:48:40: warning: 'template<class> class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
48 | template<class T> T * get_pointer(std::auto_ptr<T> const& p)
| ^~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/unique_ptr.h:59:28: note: declared here
59 | template<typename> class auto_ptr;
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:39: required from 'stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]'
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]'
93 | return f(x);
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from 'auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
83 | return apply_vector_unary<T>::reduce(x, [&](const auto& v) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
84 | if (v.size() == 0) {
| ~~~~~~~~~~~~~~~~~~~~
85 | return NEGATIVE_INFTY;
| ~~~~~~~~~~~~~~~~~~~~~~
86 | }
| ~
87 | const auto& v_ref = to_ref(v);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
88 | const double max = v_ref.maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
89 | if (!std::isfinite(max)) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
90 | return max;
| ~~~~~~~~~~~
91 | }
| ~
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
93 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here
59 | double log_sum_y = log_sum_exp(log_y);
| ~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from 'stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]'
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]'
93 | return f(x);
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from 'auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
83 | return apply_vector_unary<T>::reduce(x, [&](const auto& v) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
84 | if (v.size() == 0) {
| ~~~~~~~~~~~~~~~~~~~~
85 | return NEGATIVE_INFTY;
| ~~~~~~~~~~~~~~~~~~~~~~
86 | }
| ~
87 | const auto& v_ref = to_ref(v);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
88 | const double max = v_ref.maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
89 | if (!std::isfinite(max)) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
90 | return max;
| ~~~~~~~~~~~
91 | }
| ~
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
93 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here
59 | double log_sum_y = log_sum_exp(log_y);
| ~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from 'stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]'
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]'
93 | return f(x);
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from 'auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
83 | return apply_vector_unary<T>::reduce(x, [&](const auto& v) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
84 | if (v.size() == 0) {
| ~~~~~~~~~~~~~~~~~~~~
85 | return NEGATIVE_INFTY;
| ~~~~~~~~~~~~~~~~~~~~~~
86 | }
| ~
87 | const auto& v_ref = to_ref(v);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
88 | const double max = v_ref.maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
89 | if (!std::isfinite(max)) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
90 | return max;
| ~~~~~~~~~~~
91 | }
| ~
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
93 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here
59 | double log_sum_y = log_sum_exp(log_y);
| ~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:52: required from 'stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]'
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]'
93 | return f(x);
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from 'auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
83 | return apply_vector_unary<T>::reduce(x, [&](const auto& v) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
84 | if (v.size() == 0) {
| ~~~~~~~~~~~~~~~~~~~~
85 | return NEGATIVE_INFTY;
| ~~~~~~~~~~~~~~~~~~~~~~
86 | }
| ~
87 | const auto& v_ref = to_ref(v);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
88 | const double max = v_ref.maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
89 | if (!std::isfinite(max)) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
90 | return max;
| ~~~~~~~~~~~
91 | }
| ~
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
93 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here
59 | double log_sum_y = log_sum_exp(log_y);
| ~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:38:59: required from here
38 | Eigen::VectorXd stddev = S_ldlt.vectorD().array().sqrt().matrix();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:75: required from here
46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z));
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:76: required from here
46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z));
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:135:41: required from here
135 | Eigen::VectorXd(F.transpose() * theta_t), V_ldlt, rng);
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/hmm_hidden_state_prob.hpp:77:52: required from here
77 | alphas.col(n) = alphas.col(n).cwiseProduct(beta);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/hmm_latent_rng.hpp:71:73: required from here
71 | probs_vec = alphas.col(n_transitions) / alphas.col(n_transitions).sum();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<Eigen::Matrix<double, -1, -1> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here
49 | return L_S.template triangularView<Eigen::Lower>() * B.transpose();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here
49 | return L_S.template triangularView<Eigen::Lower>() * B.transpose();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:42: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:32: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1> >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:25:32: required from here
25 | S_inv = ldlt_of_S.solve(S_inv);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here
27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here
27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:40: required from here
27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:47: required from here
89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:54: required from here
89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:109:64: required from here
109 | (Sigma_ldlt.matrixU().solve(X)).transpose()))
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: recursively required by substitution of 'template<int Side, class Other> const Eigen::internal::triangular_solve_retval<Side, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Other> Eigen::TriangularViewImpl<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6, Eigen::Dense>::solve(const Eigen::MatrixBase<U>&) const [with int Side = <missing>; Other = <missing>]'
108 | * (D_ldlt.matrixU().solve(
| ~~~~~~~~~~~~~~~~~~~~~~^
109 | (Sigma_ldlt.matrixU().solve(X)).transpose()))
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: required from here
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/ForwardDeclarations.h:32:48: required from 'struct Eigen::internal::accessors_level<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >'
32 | enum { has_direct_access = (traits<Derived>::Flags & DirectAccessBit) ? 1 : 0,
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here
110 | .transpose()
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here
110 | .transpose()
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:43: required from here
110 | .transpose()
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:51: required from here
111 | * D_ldlt.transpositionsP());
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:52: required from here
111 | * D_ldlt.transpositionsP());
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from 'struct stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>'
72 | apply_scalar_unary<F, T>::apply(std::declval<T>()))>;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from 'auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >; stan::require_not_var_matrix_t<Container>* <anonymous> = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t<Container>* <anonymous> = 0]'
120 | return apply_scalar_unary<lgamma_fun, T>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multinomial_logit_lpmf.hpp:39:44: required from here
39 | lp += lgamma(1 + ns_map.sum()) - lgamma(1 + ns_map).sum();
| ~~~~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/std_normal_ccdf_log.hpp:5,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob.hpp:328,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim.hpp:16:
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/std_normal_lccdf.hpp: In function 'stan::return_type_t<T> stan::math::std_normal_lccdf(const T_y&)':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/std_normal_lccdf.hpp:52: note: '-Wmisleading-indentation' is disabled from this point onwards, since column-tracking was disabled due to the size of the code/headers
52 | } else if (y_dbl > 8.25) {
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/std_normal_lccdf.hpp:52: note: adding '-flarge-source-files' will allow for more column-tracking support, at the expense of compilation time and memory
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/dump.hpp: In member function 'virtual std::vector<std::complex<double> > stan::io::dump::vals_c(const std::string&) const':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/dump.hpp:694: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<double>::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
694 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/dump.hpp:707: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<int>::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
707 | real_iter < val_i->second.first.size();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Matrix<double, -1, -1>, -1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Matrix<double, -1, -1>, -1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:102:0: required from here
102 | if (C_adj.size() > 0) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:111:0: required from here
111 | = D_adj.adjoint().template triangularView<StrictlyUpper>();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:116:0: required from here
116 | D_adj.diagonal() *= 0.5;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: required from 'class Eigen::RefBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
59 | template<typename Derived> class RefBase
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:281:76: required from 'class Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >'
281 | template<typename PlainObjectType, int Options, typename StrideType> class Ref
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:76:42: required from 'class Eigen::LLT<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>'
76 | MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
| ^~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:142:0: required from here
142 | check_pos_definite("cholesky_decompose", "m", L_factor);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from 'class stan::math::arena_matrix<Eigen::Matrix<double, -1, -1>, void>'
13 | class arena_matrix<MatrixType, require_eigen_dense_base_t<MatrixType>>
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:144:0: required from here
144 | L_A.template triangularView<Eigen::StrictlyUpper>().setZero();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cholesky_factor_constrain.hpp:42:0: required from here
42 | y_val.row(m).head(m) = x.val().segment(pos, m);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
28 | * arena_L_val.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
28 | * arena_L_val.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:32:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here
94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here
94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here
94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here
94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here
94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of 'class Eigen::SparseMatrixBase<Eigen::SparseMatrix<double, 1> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from 'class Eigen::SparseCompressedBase<Eigen::SparseMatrix<double, 1> >'
36 | class SparseCompressedBase
| ^~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: recursively required by substitution of 'template<class OtherDerived> static std::true_type stan::is_base_pointer_convertible<Eigen::EigenBase, Eigen::SparseMatrix<double, 1> >::f(const Eigen::EigenBase<Derived>*) [with OtherDerived = <missing>]'
29 | = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::value
| ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible<Eigen::EigenBase, Eigen::SparseMatrix<double, 1> >'
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: required from 'struct stan::is_eigen<Eigen::SparseMatrix<double, 1> >'
21 | : bool_constant<is_base_pointer_convertible<Eigen::EigenBase, T>::value> {};
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:301:0: required by substitution of 'template<class T> class stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type> [with T = Eigen::SparseMatrix<double, 1>]'
301 | (is_eigen<T>::value || is_kernel_expression_and_not_scalar<T>::value)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here
120 | arena_t<return_t> res = w_mat_arena.val() * value_of(b_arena);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
47 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of 'class Eigen::SparseMatrixBase<Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> > >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from 'class Eigen::SparseCompressedBase<Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> > >'
36 | class SparseCompressedBase
| ^~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from 'class Eigen::SparseMapBase<Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> >, 0>'
50 | class SparseMapBase<Derived,ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:148:7: required from 'class Eigen::SparseMapBase<Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> >, 1>'
148 | class SparseMapBase<Derived,WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:222:7: required from 'class Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> >'
222 | class Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, Options, StrideType>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:129:0: required from 'class stan::math::arena_matrix<Eigen::SparseMatrix<double, 1>, void>'
129 | class arena_matrix<MatrixType, require_eigen_sparse_base_t<MatrixType>>
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:814:0: required from 'class stan::math::vari_value<Eigen::SparseMatrix<double, 1>, void>'
814 | using InnerIterator = typename arena_matrix<PlainObject>::InnerIterator;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:419:0: required from 'const auto& stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::val() const [with T = Eigen::SparseMatrix<double, 1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
419 | inline const auto& val() const noexcept { return vi_->val(); }
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here
120 | arena_t<return_t> res = w_mat_arena.val() * value_of(b_arena);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
47 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:97:21: required from 'class Eigen::Tridiagonalization<Eigen::Matrix<double, -1, -1> >'
97 | >::type SubDiagonalReturnType;
| ^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:111:62: required from 'class Eigen::SelfAdjointEigenSolver<Eigen::Matrix<double, -1, -1> >'
111 | typedef typename TridiagonalizationType::SubDiagonalType SubDiagonalType;
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/eigendecompose_sym.hpp:40:0: required from here
40 | arena_t<eigval_return_t> eigenvals = solver.eigenvalues();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1>, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/grad.hpp:27:0: required from here
27 | g = x.adj();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from 'stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)> [with auto:169 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)>; T2 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>]'
47 | f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here
49 | var log_det = sum(log(M_ldlt.vectorD()));
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)> [with auto:169 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)>; T2 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>]'
47 | f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here
49 | var log_det = sum(log(M_ldlt.vectorD()));
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, void>::apply<stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&, const stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)>&)::<lambda(const auto:6&)> [with auto:6 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, void>::apply<stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&, const stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)>&)::<lambda(const auto:6&)>; Args = {Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0> > >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:169&)>; T2 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
47 | f(x));
| ~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here
49 | var log_det = sum(log(M_ldlt.vectorD()));
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from 'class stan::math::arena_matrix<Eigen::Matrix<double, -1, -1, 1, -1, -1>, void>'
13 | class arena_matrix<MatrixType, require_eigen_dense_base_t<MatrixType>>
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:51:0: required from here
51 | reverse_pass_callback([arena_M, log_det, arena_M_inv_transpose]() mutable {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:73:0: required from here
73 | vector_d diff = (x_d.array() - x_d.maxCoeff());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:81:0: required from here
81 | Eigen::Map<vector_d>(softmax_x_d_array, a_size) = softmax_x_d.array() / sum;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:50:0: required from here
50 | arena_powers[0] = Eigen::MatrixXd::Identity(N, N);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:53:0: required from here
53 | arena_powers[i] = arena_powers[1] * arena_powers[i - 1];
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:63:0: required from here
63 | adj_M += adj_C * arena_powers[i - 1].transpose();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here
64 | adj_C = M_val.transpose() * adj_C;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here
64 | adj_C = M_val.transpose() * adj_C;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:67:0: required from here
67 | Eigen::Map<matrix_vi>(variRefB_, M_, N_).adj() += adjB;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here
85 | adjA = -adjB * Map<matrix_d>(C_, M_, N_).transpose();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here
85 | adjA = -adjB * Map<matrix_d>(C_, M_, N_).transpose();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:25:0: required from here
25 | matrix_d M = 0.5 * (Cd + Cd.transpose());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:55:0: required from here
55 | L.col(0).tail(pull) = CPCs.val().head(pull);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from 'class stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>'
13 | class arena_matrix<MatrixType, require_eigen_dense_base_t<MatrixType>>
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:56:0: required from here
56 | arena_acc.tail(pull) = 1.0 - CPCs.val().head(pull).array().square();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1>'
56 | template<typename VectorType, int Size> class VectorBlock
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:63:0: required from here
63 | L.col(i).tail(pull) = cpc_seg * arena_acc.tail(pull).sqrt();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Array<double, -1, 1>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Array<double, -1, 1>, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock<Eigen::Array<double, -1, 1>, -1>'
56 | template<typename VectorType, int Size> class VectorBlock
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here
86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here
86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here
90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here
90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1>'
56 | template<typename VectorType, int Size> class VectorBlock
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here
90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here
90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/read_cov_matrix.hpp:56:0: required from here
56 | sds.adj() += (prod.adj().cwiseProduct(corr_L.val())).rowwise().sum();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/rows_dot_self.hpp:41:0: required from here
41 | x.adj() += (2 * res.adj()).asDiagonal() * x.val();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/svd.hpp:56:0: required from here
56 | arena_Fp.diagonal().setZero();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here
69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array())
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here
69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array())
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/svd.hpp:70:0: required from here
70 | .matrix()
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here
61 | .matrix()
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here
61 | .matrix()
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:278:47: required from 'struct Eigen::internal::traits<Eigen::DiagonalWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
278 | typedef typename DiagonalVectorType::Scalar Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from 'struct Eigen::EigenBase<Eigen::DiagonalWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
42 | typedef typename internal::traits<Derived>::StorageKind StorageKind;
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:18:7: required from 'class Eigen::DiagonalBase<Eigen::DiagonalWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
18 | class DiagonalBase : public EigenBase<Derived>
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:293:7: required from 'class Eigen::DiagonalWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
293 | class DiagonalWrapper
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:63:0: required from here
63 | + arena_U * arena_D.asDiagonal().inverse()
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here
79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here
79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here
79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:80:0: required from here
80 | v1_map.adj() += di;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here
111 | += 2 * adj_ * (v1_map.val() - Eigen::Map<vector_d>(v2_, length_));
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here
111 | += 2 * adj_ * (v1_map.val() - Eigen::Map<vector_d>(v2_, length_));
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/variance.hpp:23:0: required from here
23 | vector_d dtrs_vals = dtrs_map.val();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here
25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here
27 | Eigen::Map<vector_d>(partials, size) = 2 * diff.array() / size_m1;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here
27 | Eigen::Map<vector_d>(partials, size) = 2 * diff.array() / size_m1;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1>, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/jacobian.hpp:26:0: required from here
26 | fx = fx_var.val();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)> [with auto:11 = const Eigen::Matrix<stan::math::var_value<double>, -1, 1>]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>; Args = {const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from 'auto stan::math::value_of(EigMat&&) [with EigMat = const Eigen::Matrix<var_value<double>, -1, 1>&; stan::require_eigen_dense_base_t<EigMat>* <anonymous> = 0; stan::require_not_st_arithmetic<T>* <anonymous> = 0]'
73 | return make_holder(
| ~~~~~~~~~~~^
74 | [](auto& a) {
| ~~~~~~~~~~~~~
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
76 | },
| ~~
77 | std::forward<EigMat>(M));
| ~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/algebra_solver_fp.hpp:101:0: required from here
101 | y_dummy(stan::math::value_of(y)),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here
369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1> >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here
369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/cvodes_integrator_adjoint.hpp:604:0: required from here
604 | f_y_t_vars.adj() = -Eigen::Map<Eigen::VectorXd>(NV_DATA_S(yB), N_);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/finite_diff_hessian_times_vector_auto.hpp:62:0: required from here
62 | hvp = (grad_forward - grad_backward) / (2 * epsilon);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/initialize.hpp:7,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/diagnose/diagnose.hpp:10,
from D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:49:
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/random_var_context.hpp: In member function 'virtual std::vector<std::complex<double> > stan::io::random_var_context::vals_c(const std::string&) const':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/random_var_context.hpp:111: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<double>::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
111 | for (comp_iter = 0, real_iter = 0; real_iter < val_r.size();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:182:0: required from here
182 | return normal_fullrank(Eigen::VectorXd(mu_.array().square()),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:183:0: required from here
183 | Eigen::MatrixXd(L_chol_.array().square()));
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:197:0: required from here
197 | return normal_fullrank(Eigen::VectorXd(mu_.array().sqrt()),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:198:0: required from here
198 | Eigen::MatrixXd(L_chol_.array().sqrt()));
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:263:0: required from here
263 | L_chol_.array() /= rhs.L_chol().array();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here
351 | return (L_chol_ * eta) + mu_;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here
351 | return (L_chol_ * eta) + mu_;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:459:0: required from here
459 | L_grad.diagonal().array() += L_chol_.diagonal().array().inverse();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here
314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here
314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here
314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:370:0: required from here
370 | omega_grad.array() += tmp_mu_grad.array().cwiseProduct(eta.array());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:388:0: required from here
388 | omega_grad.array() = omega_grad.array().cwiseProduct(omega_.array().exp());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/nuts/base_nuts.hpp:175:0: required from here
175 | rho = rho_bck + rho_fwd;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0, 6>'
126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, 1>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0> >'
179 | typedef typename internal::find_best_packet<Scalar,SizeAtCompileTime>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0, 6>'
126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1> >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:53:0: required from here
53 | z.p = z.inv_e_metric_.llt().matrixU().solve(u);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_matrix.hpp:133:17: required from 'auto stan::math::to_matrix(const std::vector<T>&, int, int) [with T = double]'
133 | return Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>(
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
134 | &x[0], m, n);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/read_dense_inv_metric.hpp:33:0: required from here
33 | inv_metric = stan::math::to_matrix(dense_vals, num_params, num_params);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:27:0: required from here
27 | covar = (n / (n + 5.0)) * covar
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here
29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here
29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: recursively required by substitution of 'template<class OtherDerived> typename Eigen::ScalarBinaryOpTraits<double, typename Eigen::internal::traits<T>::Scalar, Eigen::internal::scalar_product_op<double, typename Eigen::internal::traits<T>::Scalar> >::ReturnType Eigen::MatrixBase<Eigen::Matrix<double, -1, 1> >::dot(const Eigen::MatrixBase<Derived>&) const [with OtherDerived = <missing>]'
21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from here
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:27:0: required from here
27 | var = (n / (n + 5.0)) * var
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here
28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here
28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size());
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:7,
from D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:68:
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp: In member function 'virtual std::vector<std::complex<double> > stan::io::array_var_context::vals_c(const std::string&) const':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp:304: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<double>::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
304 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp:317: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<int>::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
317 | real_iter < val_i->second.first.size();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Matrix<double, -1, -1>, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from here
72 | Eigen::Map<Eigen::VectorXd>(&row[0], draws.cols()) = draws.row(i);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 1>'
223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from 'class stan::math::arena_matrix<Eigen::Matrix<double, 1, -1>, void>'
13 | class arena_matrix<MatrixType, require_eigen_dense_base_t<MatrixType>>
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue_varmat.hpp:145:0: required from here
145 | x_ret_vals.coeffRef(j) = x.val().coeff(row_idx_val, col_idx_vals[j]);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:28:12: required from 'auto stan::math::multiply(const Mat&, Scal) [with Mat = Eigen::Matrix<double, -1, 1>; Scal = int; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_not_st_var<Scal, Mat>* <anonymous> = 0; stan::require_all_not_complex_t<Scal, typename stan::value_type<T, void>::type>* <anonymous> = 0]'
28 | return c * m;
| ~~^~~
stanExports_stanmarg.h:3508:0: required from here
3508 | stan::math::multiply(stan::math::to_vector(clus_size_ns), N_between)),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:84:12: required from 'auto stan::math::multiply(Scal, const Mat&) [with Scal = int; Mat = Eigen::Matrix<double, -1, -1>; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::require_all_not_complex_t<Scal, typename stan::value_type<T_actual, void>::type>* <anonymous> = 0]'
84 | return c * m;
| ~~^~~
stanExports_stanmarg.h:14328:0: required from here
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, 1>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Matrix<double, -1, 1>, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>'
56 | template<typename VectorType, int Size> class VectorBlock
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:187:0: required from 'auto stan::model::rvalue(Vec&&, const char*, index_min_max) [with Vec = const Eigen::Matrix<double, -1, 1>&; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_not_std_vector_t<T_y>* <anonymous> = 0]'
187 | return v.segment(slice_start, slice_size);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:697:0: required from 'auto stan::model::rvalue(StdVec&, const char*, index_uni, const Idxs& ...) [with StdVec = const std::vector<Eigen::Matrix<double, -1, 1> >; Idxs = {index_min_max}; stan::require_std_vector_t<T>* <anonymous> = 0]'
697 | return rvalue(v[idx1.n_ - 1], name, idxs...);
stanExports_stanmarg.h:14486:0: required from here
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, -1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Matrix<double, -1, -1>, -1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:376:0: required from 'auto stan::model::rvalue(Mat&&, const char*, index_min_max, index_min_max) [with Mat = const Eigen::Matrix<double, -1, -1>&; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
376 | return x.block(row_idx.min_ - 1, col_idx.min_ - 1,
377 | row_idx.max_ - (row_idx.min_ - 1),
378 | col_idx.max_ - (col_idx.min_ - 1));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:697:0: required from 'auto stan::model::rvalue(StdVec&, const char*, index_uni, const Idxs& ...) [with StdVec = const std::vector<Eigen::Matrix<double, -1, -1> >; Idxs = {index_min_max, index_min_max}; stan::require_std_vector_t<T>* <anonymous> = 0]'
697 | return rvalue(v[idx1.n_ - 1], name, idxs...);
stanExports_stanmarg.h:14491:0: required from here
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:158:0: required from 'stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)> [with auto:767 = const Eigen::Matrix<double, -1, 1>]'
158 | return plain_type_t<EigVec>::NullaryExpr(
159 | idx.ns_.size(), [name, &idx, &v_ref](Eigen::Index i) {
160 | math::check_range("vector[multi] indexing", name, v_ref.size(),
161 | idx.ns_[i]);
162 | return v_ref.coeff(idx.ns_[i] - 1);
163 | });
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>; Args = {const Eigen::Matrix<double, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:156:0: required from 'auto stan::model::rvalue(EigVec&&, const char*, const index_multi&) [with EigVec = const Eigen::Matrix<double, -1, 1>&; stan::require_eigen_vector_t<C>* <anonymous> = 0]'
156 | return stan::math::make_holder(
157 | [name, &idx](auto& v_ref) {
158 | return plain_type_t<EigVec>::NullaryExpr(
159 | idx.ns_.size(), [name, &idx, &v_ref](Eigen::Index i) {
160 | math::check_range("vector[multi] indexing", name, v_ref.size(),
161 | idx.ns_[i]);
162 | return v_ref.coeff(idx.ns_[i] - 1);
163 | });
164 | },
165 | stan::math::to_ref(v));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:697:0: required from 'auto stan::model::rvalue(StdVec&, const char*, index_uni, const Idxs& ...) [with StdVec = const std::vector<Eigen::Matrix<double, -1, 1> >; Idxs = {index_multi}; stan::require_std_vector_t<T>* <anonymous> = 0]'
697 | return rvalue(v[idx1.n_ - 1], name, idxs...);
stanExports_stanmarg.h:14526:0: required from here
14526 | stan::model::rvalue(YXbarstar, "YXbarstar",
14527 | stan::model::index_uni(mm),
14528 | stan::model::index_multi(
14529 | stan::model::rvalue(xdatidx, "xdatidx",
14530 | stan::model::index_min_max(1,
14531 | stan::model::rvalue(Nx, "Nx",
14532 | stan::model::index_uni(mm)))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int>&)::<lambda(auto:315&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int>&)::<lambda(auto:315&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int>&)::<lambda(auto:315&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int>&)::<lambda(auto:315&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int>&)::<lambda(auto:315&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:102:18: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::return_type_t<T1, T2> = double]'
102 | x.unaryExpr([lb, &lp](auto&& xx) { return lb_constrain(xx, lb, lp); }));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<double, -1, 1>; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:14992:0: required from here
14991 | Theta_sd_free = in__.template read_constrain_lb<
14992 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
14993 | lp__, Theta_sd_free_1dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&&, const int&)::<lambda(auto:314&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&&, const int&)::<lambda(auto:314&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&&, const int&)::<lambda(auto:314&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&&, const int&)::<lambda(auto:314&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::lb_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&&, const int&)::<lambda(auto:314&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:83:26: required from 'auto stan::math::lb_constrain(T&&, L&&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; L = const int&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
83 | return eval(x.unaryExpr([lb](auto&& x) { return lb_constrain(x, lb); }));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:388:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<double, -1, 1>; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]'
388 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb);
stanExports_stanmarg.h:14992:0: required from here
14991 | Theta_sd_free = in__.template read_constrain_lb<
14992 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
14993 | lp__, Theta_sd_free_1dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>&)::<lambda(auto:349&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>&)::<lambda(auto:349&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>&)::<lambda(auto:349&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>&)::<lambda(auto:349&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t<Eigen::Map<const Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>&)::<lambda(auto:349&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_constrain.hpp:133:26: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_not_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = double]'
133 | return eval(x.unaryExpr(
| ~~~~~~~~~~~^
134 | [lb, ub, &lp](auto&& xx) { return lub_constrain(xx, lb, ub, lp); }));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<double, -1, 1>; bool Jacobian = false; LB = int; UB = int; LP = double; Sizes = {int}; T = double]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:14999:0: required from here
14998 | Theta_r_free = in__.template read_constrain_lub<
14999 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
15000 | 1, lp__, Theta_r_free_1dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::<lambda(auto:348&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::<lambda(auto:348&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::<lambda(auto:348&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::<lambda(auto:348&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::lub_constrain<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::<lambda(auto:348&&)>, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_constrain.hpp:122:18: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_not_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0]'
122 | x.unaryExpr([ub, lb](auto&& xx) { return lub_constrain(xx, lb, ub); }));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:443:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<double, -1, 1>; bool Jacobian = false; LB = int; UB = int; LP = double; Sizes = {int}; T = double]'
443 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub);
stanExports_stanmarg.h:14999:0: required from here
14998 | Theta_r_free = in__.template read_constrain_lub<
14999 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
15000 | 1, lp__, Theta_r_free_1dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:15526:0: required from here
15526 | stan::math::add(
15527 | stan::model::rvalue(T_r_lower, "T_r_lower",
15528 | stan::model::index_uni(g)),
15529 | stan::math::transpose(
15530 | stan::model::rvalue(T_r_lower, "T_r_lower",
15531 | stan::model::index_uni(g)))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Mat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:15525:0: required from here
15525 | stan::math::subtract(
15526 | stan::math::add(
15527 | stan::model::rvalue(T_r_lower, "T_r_lower",
15528 | stan::model::index_uni(g)),
15529 | stan::math::transpose(
15530 | stan::model::rvalue(T_r_lower, "T_r_lower",
15531 | stan::model::index_uni(g)))),
15532 | stan::math::diag_matrix(stan::math::rep_vector(1, p))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:15739:0: required from here
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::Matrix<double, -1, -1, 1, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:15780:0: required from here
15780 | stan::math::add(
15781 | stan::model::deep_copy(
15782 | stan::model::rvalue(Sigma, "Sigma",
15783 | stan::model::index_uni(g),
15784 | stan::model::index_min_max(1, p),
15785 | stan::model::index_min_max(1, p))),
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Matrix<double, -1, 1>, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>'
56 | template<typename VectorType, int Size> class VectorBlock
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:187:0: required from 'auto stan::model::rvalue(Vec&&, const char*, index_min_max) [with Vec = Eigen::Matrix<double, -1, 1>&; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_not_std_vector_t<T_y>* <anonymous> = 0]'
187 | return v.segment(slice_start, slice_size);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:697:0: required from 'auto stan::model::rvalue(StdVec&, const char*, index_uni, const Idxs& ...) [with StdVec = std::vector<Eigen::Matrix<double, -1, 1> >; Idxs = {index_min_max}; stan::require_std_vector_t<T>* <anonymous> = 0]'
697 | return rvalue(v[idx1.n_ - 1], name, idxs...);
stanExports_stanmarg.h:15800:0: required from here
15800 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(g),
15801 | stan::model::index_min_max(1, p))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1>; stan::require_all_eigen_vt<std::is_arithmetic, Mat1, Mat2>* <anonymous> = 0; stan::require_not_eigen_row_and_col_t<Mat1, Mat2>* <anonymous> = 0]'
107 | return m1 * m2;
| ~~~^~~~
stanExports_stanmarg.h:15803:0: required from here
15803 | stan::math::multiply(
15804 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15805 | stan::model::index_uni(g)),
15806 | stan::model::rvalue(Alpha, "Alpha",
15807 | stan::model::index_uni(g),
15808 | stan::model::index_min_max(1, m),
15809 | stan::model::index_uni(1))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:17365:0: required from here
17365 | stan::math::add(
17366 | stan::model::deep_copy(
17367 | stan::model::rvalue(S_PW_rep_full, "S_PW_rep_full",
17368 | stan::model::index_uni(gg))),
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:17381:0: required from here
17381 | stan::math::add(
17382 | stan::model::deep_copy(
17383 | stan::model::rvalue(S_B_rep, "S_B_rep",
17384 | stan::model::index_uni(gg))),
17385 | stan::math::multiply(
17386 | stan::model::rvalue(cluster_size, "cluster_size",
17387 | stan::model::index_uni(clusidx)),
17388 | stan::math::tcrossprod(
17389 | stan::math::to_matrix(
17390 | stan::math::subtract(
17391 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17392 | stan::model::index_uni(clusidx)),
17393 | stan::model::rvalue(ov_mean_rep, "ov_mean_rep",
17394 | stan::model::index_uni(gg))))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:158:0: required from 'stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)> [with auto:767 = Eigen::Matrix<double, -1, 1>]'
158 | return plain_type_t<EigVec>::NullaryExpr(
159 | idx.ns_.size(), [name, &idx, &v_ref](Eigen::Index i) {
160 | math::check_range("vector[multi] indexing", name, v_ref.size(),
161 | idx.ns_[i]);
162 | return v_ref.coeff(idx.ns_[i] - 1);
163 | });
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:156:0: required from 'auto stan::model::rvalue(EigVec&&, const char*, const index_multi&) [with EigVec = Eigen::Matrix<double, -1, 1>&; stan::require_eigen_vector_t<C>* <anonymous> = 0]'
156 | return stan::math::make_holder(
157 | [name, &idx](auto& v_ref) {
158 | return plain_type_t<EigVec>::NullaryExpr(
159 | idx.ns_.size(), [name, &idx, &v_ref](Eigen::Index i) {
160 | math::check_range("vector[multi] indexing", name, v_ref.size(),
161 | idx.ns_[i]);
162 | return v_ref.coeff(idx.ns_[i] - 1);
163 | });
164 | },
165 | stan::math::to_ref(v));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:697:0: required from 'auto stan::model::rvalue(StdVec&, const char*, index_uni, const Idxs& ...) [with StdVec = std::vector<Eigen::Matrix<double, -1, 1> >; Idxs = {index_multi}; stan::require_std_vector_t<T>* <anonymous> = 0]'
697 | return rvalue(v[idx1.n_ - 1], name, idxs...);
stanExports_stanmarg.h:17407:0: required from here
17407 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17408 | stan::model::index_uni(clusidx),
17409 | stan::model::index_multi(
17410 | stan::model::rvalue(between_idx,
17411 | "between_idx",
17412 | stan::model::index_min_max(1, N_between)))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:17406:0: required from here
17406 | stan::math::subtract(
17407 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17408 | stan::model::index_uni(clusidx),
17409 | stan::model::index_multi(
17410 | stan::model::rvalue(between_idx,
17411 | "between_idx",
17412 | stan::model::index_min_max(1, N_between)))),
17413 | stan::model::rvalue(xbar_b_rep, "xbar_b_rep",
17414 | stan::model::index_uni(gg),
17415 | stan::model::index_multi(
17416 | stan::model::rvalue(between_idx,
17417 | "between_idx",
17418 | stan::model::index_min_max(1, N_between)))))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:17592:0: required from here
17592 | stan::math::subtract(
17593 | stan::model::rvalue(S_B_rep, "S_B_rep",
17594 | stan::model::index_uni(gg)),
17595 | stan::model::rvalue(S_PW_rep_full, "S_PW_rep_full",
17596 | stan::model::index_uni(gg)))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:84:12: required from 'auto stan::math::multiply(Scal, const Mat&) [with Scal = double; Mat = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::require_all_not_complex_t<Scal, typename stan::value_type<T_actual, void>::type>* <anonymous> = 0]'
84 | return c * m;
| ~~^~~
stanExports_stanmarg.h:17588:0: required from here
17588 | stan::math::multiply(
17589 | stan::math::pow(
17590 | stan::model::rvalue(gs, "gs",
17591 | stan::model::index_uni(gg)), -1),
17592 | stan::math::subtract(
17593 | stan::model::rvalue(S_B_rep, "S_B_rep",
17594 | stan::model::index_uni(gg)),
17595 | stan::model::rvalue(S_PW_rep_full, "S_PW_rep_full",
17596 | stan::model::index_uni(gg)))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>&>(const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>&)::<lambda(auto:13&)> [with auto:13 = const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>&>(const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>&)::<lambda(auto:13&)>; Args = {const Eigen::Block<Eigen::Matrix<double, -1, -1, 0, -1, -1>, -1, 1, true>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: required from 'auto stan::math::as_array_or_scalar(T&&) [with T = const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>&; <template-parameter-1-2> = void; stan::require_not_eigen_array_t<T>* <anonymous> = 0]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:29: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; T2 = int; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~^~~
stanExports_stanmarg.h:17872:0: required from here
17872 | stan::math::divide(
17873 | stan::model::rvalue(satout, "satout",
17874 | stan::model::index_uni(g),
17875 | stan::model::index_omni(),
17876 | stan::model::index_uni(1)),
17877 | stan::model::rvalue(N, "N", stan::model::index_uni(g))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:33: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; T2 = int; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17872:0: required from here
17872 | stan::math::divide(
17873 | stan::model::rvalue(satout, "satout",
17874 | stan::model::index_uni(g),
17875 | stan::model::index_omni(),
17876 | stan::model::index_uni(1)),
17877 | stan::model::rvalue(N, "N", stan::model::index_uni(g))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:64: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; T2 = int; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:17872:0: required from here
17872 | stan::math::divide(
17873 | stan::model::rvalue(satout, "satout",
17874 | stan::model::index_uni(g),
17875 | stan::model::index_omni(),
17876 | stan::model::index_uni(1)),
17877 | stan::model::rvalue(N, "N", stan::model::index_uni(g))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Matrix<double, -1, -1>, -1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<Eigen::Matrix<double, -1, -1>, -1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:661:0: required from 'auto stan::model::rvalue(Mat&&, const char*, const Idx&, index_min_max) [with Mat = Eigen::Matrix<double, -1, -1>&; Idx = index_omni; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
661 | return rvalue(x.middleCols(col_start, col_idx.max_ - col_start), name,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:697:0: required from 'auto stan::model::rvalue(StdVec&, const char*, index_uni, const Idxs& ...) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; Idxs = {index_omni, index_min_max}; stan::require_std_vector_t<T>* <anonymous> = 0]'
697 | return rvalue(v[idx1.n_ - 1], name, idxs...);
stanExports_stanmarg.h:17883:0: required from here
17883 | stan::model::rvalue(satout, "satout",
17884 | stan::model::index_uni(g),
17885 | stan::model::index_omni(),
17886 | stan::model::index_min_max(2, ((p + q) + 1))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>&>(const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>&)::<lambda(auto:13&)> [with auto:13 = const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>&>(const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>&)::<lambda(auto:13&)>; Args = {const Eigen::Block<Eigen::Matrix<double, -1, -1, 0, -1, -1>, -1, -1, true>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: required from 'auto stan::math::as_array_or_scalar(T&&) [with T = const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>&; <template-parameter-1-2> = void; stan::require_not_eigen_array_t<T>* <anonymous> = 0]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:29: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; T2 = int; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~^~~
stanExports_stanmarg.h:17882:0: required from here
17882 | stan::math::divide(
17883 | stan::model::rvalue(satout, "satout",
17884 | stan::model::index_uni(g),
17885 | stan::model::index_omni(),
17886 | stan::model::index_min_max(2, ((p + q) + 1))),
17887 | stan::model::rvalue(N, "N",
17888 | stan::model::index_uni(g))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:33: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; T2 = int; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17882:0: required from here
17882 | stan::math::divide(
17883 | stan::model::rvalue(satout, "satout",
17884 | stan::model::index_uni(g),
17885 | stan::model::index_omni(),
17886 | stan::model::index_min_max(2, ((p + q) + 1))),
17887 | stan::model::rvalue(N, "N",
17888 | stan::model::index_uni(g))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:64: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; T2 = int; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:17882:0: required from here
17882 | stan::math::divide(
17883 | stan::model::rvalue(satout, "satout",
17884 | stan::model::index_uni(g),
17885 | stan::model::index_omni(),
17886 | stan::model::index_min_max(2, ((p + q) + 1))),
17887 | stan::model::rvalue(N, "N",
17888 | stan::model::index_uni(g))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/transpose.hpp:18:21: required from 'auto stan::math::transpose(const T&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_matrix_t<T>* <anonymous> = 0]'
18 | return m.transpose();
| ~~~~~~~~~~~^~
stanExports_stanmarg.h:17892:0: required from here
17892 | stan::math::transpose(
17893 | stan::model::rvalue(Mu_sat, "Mu_sat",
17894 | stan::model::index_uni(g))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, 1>; Mat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_vt<std::is_arithmetic, Mat1, Mat2>* <anonymous> = 0; stan::require_not_eigen_row_and_col_t<Mat1, Mat2>* <anonymous> = 0]'
107 | return m1 * m2;
| ~~~^~~~
stanExports_stanmarg.h:17889:0: required from here
17889 | stan::math::multiply(
17890 | stan::model::rvalue(Mu_sat, "Mu_sat",
17891 | stan::model::index_uni(g)),
17892 | stan::math::transpose(
17893 | stan::model::rvalue(Mu_sat, "Mu_sat",
17894 | stan::model::index_uni(g))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >, const Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >, const Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >, const Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >, const Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >, const Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >; Mat2 = Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:17881:0: required from here
17881 | stan::math::subtract(
17882 | stan::math::divide(
17883 | stan::model::rvalue(satout, "satout",
17884 | stan::model::index_uni(g),
17885 | stan::model::index_omni(),
17886 | stan::model::index_min_max(2, ((p + q) + 1))),
17887 | stan::model::rvalue(N, "N",
17888 | stan::model::index_uni(g))),
17889 | stan::math::multiply(
17890 | stan::model::rvalue(Mu_sat, "Mu_sat",
17891 | stan::model::index_uni(g)),
17892 | stan::math::transpose(
17893 | stan::model::rvalue(Mu_sat, "Mu_sat",
17894 | stan::model::index_uni(g))))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/transpose.hpp:18:21: required from 'auto stan::math::transpose(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; stan::require_matrix_t<T>* <anonymous> = 0]'
18 | return m.transpose();
| ~~~~~~~~~~~^~
stanExports_stanmarg.h:18015:0: required from here
18015 | stan::math::transpose(
18016 | stan::math::subtract(
18017 | stan::model::rvalue(YXstar, "YXstar",
18018 | stan::model::index_uni(jj)),
18019 | stan::model::rvalue(Mu_sat, "Mu_sat",
18020 | stan::model::index_uni(grpidx)))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:33: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Matrix<double, -1, -1>; T2 = int; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
18037 | stan::model::rvalue(N, "N",
18038 | stan::model::index_uni(grpidx))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, -1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:64: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Matrix<double, -1, -1>; T2 = int; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
18037 | stan::model::rvalue(N, "N",
18038 | stan::model::index_uni(grpidx))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1>'
56 | template<typename VectorType, int Size> class VectorBlock
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:187:0: required from 'auto stan::model::rvalue(Vec&&, const char*, index_min_max) [with Vec = const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_not_std_vector_t<T_y>* <anonymous> = 0]'
187 | return v.segment(slice_start, slice_size);
stanExports_stanmarg.h:18218:0: required from here
18218 | stan::model::rvalue(log_lik_x_full, "log_lik_x_full",
18219 | stan::model::index_min_max(r1, r2))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, 1>; Mat2 = Eigen::VectorBlock<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:18214:0: required from here
18214 | stan::math::subtract(
18215 | stan::model::deep_copy(
18216 | stan::model::rvalue(log_lik, "log_lik",
18217 | stan::model::index_min_max(r1, r2))),
18218 | stan::model::rvalue(log_lik_x_full, "log_lik_x_full",
18219 | stan::model::index_min_max(r1, r2))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, 1>; Mat2 = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:18705:0: required from here
18705 | stan::math::subtract(
18706 | stan::model::deep_copy(
18707 | stan::model::rvalue(log_lik_rep, "log_lik_rep",
18708 | stan::model::index_min_max(rr1, rr2))),
18709 | stan::model::rvalue(log_lik_x_rep, "log_lik_x_rep",
18710 | stan::model::index_min_max(rr1, rr2))),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, 3>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<double, 3, 1> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Array.h:17:8: required from 'struct Eigen::internal::traits<Eigen::Array<double, 3, 1> >'
17 | struct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Array<double, 3, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from 'class Eigen::Array<double, 3, 1>'
45 | class Array
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
28 | ArrayAT a_array = as_array_or_scalar(a);
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Array<double, 3, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Array<double, 3, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Array<double, 3, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Array<double, 3, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Array<double, 3, 1> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Array<double, 3, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from 'class Eigen::Array<double, 3, 1>'
45 | class Array
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
28 | ArrayAT a_array = as_array_or_scalar(a);
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar<const std::vector<double>&>(const std::vector<double>&)::<lambda(auto:14&)>; Args = {const std::vector<double, std::allocator<double> >&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:72:21: required from 'auto stan::math::as_array_or_scalar(T&&) [with T = const std::vector<double>&; stan::require_std_vector_t<T>* <anonymous> = 0; stan::require_not_std_vector_t<typename stan::value_type<T>::type>* <anonymous> = 0]'
72 | return make_holder([](auto& x) { return T_map(x.data(), x.size()); },
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
73 | std::forward<T>(v));
| ~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:39: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
28 | ArrayAT a_array = as_array_or_scalar(a);
| ~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:43: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk));
| ~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from 'class Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >'
52 | class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type,
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:55: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk));
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from 'stan::math::fabs<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >(const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >&)::<lambda(const auto:9&)> [with auto:9 = Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >]'
67 | x, [](const auto& v) { return v.array().abs(); });
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::fabs<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >(const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >&)::<lambda(const auto:9&)>; T2 = Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >; stan::require_t<stan::is_eigen_array<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >]'
53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/fabs.hpp:66:46: required from 'auto stan::math::fabs(const Container&) [with Container = Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
66 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
67 | x, [](const auto& v) { return v.array().abs(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:37: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk));
| ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >&)::<lambda(const auto:169&)> [with auto:169 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >&)::<lambda(const auto:169&)>; T2 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >; stan::require_t<stan::is_eigen_array<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >]'
53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:49:25: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
49 | T_return p = sum(log(abs_apk)) - sum(log(abs_bpk));
| ~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:75: required from 'stan::return_type_t<T> stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t<T>* <anonymous> = 0; stan::return_type_t<T> = double]'
58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here
16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {}
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:32: required from 'stan::return_type_t<T> stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t<T>* <anonymous> = 0; stan::return_type_t<T> = double]'
58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2));
| ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here
16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {}
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from 'struct stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>'
72 | apply_scalar_unary<F, T>::apply(std::declval<T>()))>;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from 'auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; stan::require_not_var_matrix_t<Container>* <anonymous> = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t<Container>* <anonymous> = 0]'
120 | return apply_scalar_unary<lgamma_fun, T>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:29: required from 'stan::return_type_t<T> stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t<T>* <anonymous> = 0; stan::return_type_t<T> = double]'
58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2));
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here
16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {}
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here
28 | double variance = diff.squaredNorm() / size_m1;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, -1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, -1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, -1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Array<double, -1, -1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Array<double, -1, -1> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Array<double, -1, -1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from 'class Eigen::Array<double, -1, -1>'
45 | class Array
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from 'Derived& Eigen::ArrayBase<Derived>::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >; Scalar = double]'
27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here
280 | L_chol_.array() += scalar;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, -1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from 'Derived& Eigen::ArrayBase<Derived>::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >; Scalar = double]'
27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here
280 | L_chol_.array() += scalar;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of 'std::vector<long long unsigned int> stan::io::array_var_context::validate_dims(const std::vector<std::__cxx11::basic_string<char> >&, T, const std::vector<std::vector<long long unsigned int> >&) [with T = long long unsigned int]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp:97:0: required from here
97 | std::vector<size_t> dim_vec = validate_dims(names, values.size(), dims);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<std::vector<long long unsigned int> >::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
74 | for (int i = 0; i < dims.size(); i++) {
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of 'std::vector<long long unsigned int> stan::io::array_var_context::validate_dims(const std::vector<std::__cxx11::basic_string<char> >&, T, const std::vector<std::vector<long long unsigned int> >&) [with T = long long int]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here
118 | std::vector<size_t> dim_vec = validate_dims(names, values.size(), dims);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector<std::vector<long long unsigned int> >::size_type' {aka 'long long unsigned int'} [-Wsign-compare]
74 | for (int i = 0; i < dims.size(); i++) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:110:27: required from 'stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:1&)> [with auto:1 = Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >]'
110 | return m.unaryExpr([](auto x) { return value_of_rec(x); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:1&)>; Args = {Eigen::Map<const Eigen::Array<int, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:108:21: required from 'auto stan::math::value_of_rec(T&&) [with T = Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >; <template-parameter-1-2> = void; <template-parameter-1-3> = void]'
108 | return make_holder(
| ~~~~~~~~~~~^
109 | [](auto& m) {
| ~~~~~~~~~~~~~
110 | return m.unaryExpr([](auto x) { return value_of_rec(x); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | },
| ~~
112 | std::forward<T>(M));
| ~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_greater_or_equal.hpp:157:30: required from 'void stan::math::check_greater_or_equal(const char*, const char*, const T_y&, const T_low&, Idxs ...) [with T_y = std::vector<int>; T_low = int; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_not_std_vector_vt<stan::is_container_or_var_matrix, T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; Idxs = {}]'
157 | auto&& y_arr = value_of_rec(as_array_or_scalar(to_ref(y)));
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:5537:0: required from here
5537 | stan::math::check_greater_or_equal(function__, "N", N, 1);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tanh.hpp:59:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tanh.hpp:58:46: required from 'auto stan::math::tanh(const Container&) [with Container = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
58 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
59 | x, [](const auto& v) { return v.array().tanh(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_constrain.hpp:47:34: required from 'auto stan::math::corr_constrain(const T_x&, T_lp&) [with T_x = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_lp = double]'
47 | plain_type_t<T_x> tanh_x = tanh(x);
| ~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tanh.hpp:59:51: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tanh.hpp:58:46: required from 'auto stan::math::tanh(const Container&) [with Container = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
58 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
59 | x, [](const auto& v) { return v.array().tanh(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_constrain.hpp:47:34: required from 'auto stan::math::corr_constrain(const T_x&, T_lp&) [with T_x = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_lp = double]'
47 | plain_type_t<T_x> tanh_x = tanh(x);
| ~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, void>::apply<stan::math::tanh<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(const auto:246&)> >(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&, const stan::math::tanh<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >(const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(const auto:246&)>&)::<lambda(const auto:6&)> [with auto:6 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_tanh_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tanh.hpp:58:46: required from 'auto stan::math::tanh(const Container&) [with Container = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
58 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
59 | x, [](const auto& v) { return v.array().tanh(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_constrain.hpp:47:34: required from 'auto stan::math::corr_constrain(const T_x&, T_lp&) [with T_x = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_lp = double]'
47 | plain_type_t<T_x> tanh_x = tanh(x);
| ~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary<Eigen::Matrix<double, -1, 1>, void>::apply<stan::math::square<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:239&)> >(const Eigen::Matrix<double, -1, 1>&, const stan::math::square<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:239&)>&)::<lambda(const auto:6&)> [with auto:6 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/square.hpp:69:46: required from 'auto stan::math::square(const Container&) [with Container = Eigen::Matrix<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
69 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
70 | x, [](const auto& v) { return v.array().square(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_constrain.hpp:48:25: required from 'auto stan::math::corr_constrain(const T_x&, T_lp&) [with T_x = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_lp = double]'
48 | lp += sum(log1m(square(tanh_x)));
| ~~~~~~^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, void>::apply(const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, void>::apply(const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, void>::apply(const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, void>::apply(const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, void>::apply(const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(auto:3&&)>, const Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log1m.hpp:74:49: required from 'auto stan::math::log1m(const T&) [with T = Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_not_var_matrix_t<Container>* <anonymous> = 0; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<Container>* <anonymous> = 0]'
74 | return apply_scalar_unary<log1m_fun, T>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_constrain.hpp:48:18: required from 'auto stan::math::corr_constrain(const T_x&, T_lp&) [with T_x = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_lp = double]'
48 | lp += sum(log1m(square(tanh_x)));
| ~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
stanExports_stanmarg.h: In instantiation of 'void model_stanmarg_namespace::model_stanmarg::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; VecI = std::vector<int>; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]':
stanExports_stanmarg.h:22517:0: required from here
22517 | unconstrain_array_impl(params_constrained, params_i,
22518 | params_unconstrained, pstream);
stanExports_stanmarg.h:19334: warning: variable 'pos__' set but not used [-Wunused-but-set-variable]
19334 | int pos__ = std::numeric_limits<int>::min();
stanExports_stanmarg.h: In instantiation of 'void model_stanmarg_namespace::model_stanmarg::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = Eigen::Matrix<double, -1, 1>; VecI = std::vector<int>; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]':
stanExports_stanmarg.h:22527:0: required from here
22527 | unconstrain_array_impl(params_constrained, params_i,
22528 | params_unconstrained, pstream);
stanExports_stanmarg.h:19334: warning: variable 'pos__' set but not used [-Wunused-but-set-variable]
19334 | int pos__ = std::numeric_limits<int>::min();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp: In instantiation of 'SEXPREC* rstan::stan_fit<Model, RNG_t>::standalone_gqs(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]':
stanExports_stanmarg.cc:30:0: required from here
30 | .method("standalone_gqs", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::standalone_gqs)
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1252: warning: variable 'ret' set but not used [-Wunused-but-set-variable]
1252 | int ret = stan::services::error_codes::CONFIG;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, 2>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<double, 2, 1> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 2, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, 2, 1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from 'stan::return_type_t<Ta1, Ta1, Tb, Tz> stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]'
181 | Eigen::Matrix<double, 2, 1> a_args(2);
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from 'TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double, double>]'
190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from 'auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t<std::integral_constant<bool, __v> >* <anonymous> = 0]'
306 | return internal::grad_2F1_impl<true, true, true, true>(a1, a2, b1, z,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
307 | precision, max_steps);
| ~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here
37 | = grad_2F1<true>(a + b, 1.0, a + 1, z);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 2, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 2, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 2, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 2, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 2, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 2, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, 2, 1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from 'stan::return_type_t<Ta1, Ta1, Tb, Tz> stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]'
181 | Eigen::Matrix<double, 2, 1> a_args(2);
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from 'TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double, double>]'
190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from 'auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t<std::integral_constant<bool, __v> >* <anonymous> = 0]'
306 | return internal::grad_2F1_impl<true, true, true, true>(a1, a2, b1, z,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
307 | precision, max_steps);
| ~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here
37 | = grad_2F1<true>(a + b, 1.0, a + 1, z);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, 1, 0, 1, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, 1, 0, 1, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, 1, 0, 1, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 1, 1, 0, 1, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 1, 1, 0, 1, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 1, 1, 0, 1, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, 1, 1, 0, 1, 1>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:182:31: required from 'stan::return_type_t<Ta1, Ta1, Tb, Tz> stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]'
182 | Eigen::Matrix<double, 1, 1> b_args(1);
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from 'TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double, double>]'
190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from 'auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t<std::integral_constant<bool, __v> >* <anonymous> = 0]'
306 | return internal::grad_2F1_impl<true, true, true, true>(a1, a2, b1, z,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
307 | precision, max_steps);
| ~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here
37 | = grad_2F1<true>(a + b, 1.0, a + 1, z);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:117:39: required from 'TupleT stan::math::internal::grad_2F1_impl_ab(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double>]'
117 | inner_diff = g_current.array().abs().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:204:78: required from 'TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double, double>]'
204 | grad_tuple_ab = grad_2F1_impl_ab<calc_a1_euler, calc_a2_euler, calc_b1>(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
205 | a1_euler, a2_euler, b1, z_euler);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from 'auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t<std::integral_constant<bool, __v> >* <anonymous> = 0]'
306 | return internal::grad_2F1_impl<true, true, true, true>(a1, a2, b1, z,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
307 | precision, max_steps);
| ~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here
37 | = grad_2F1<true>(a + b, 1.0, a + 1, z);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/plugins/CommonCwiseUnaryOps.h:62:1: required by substitution of 'template<class NewType> typename Eigen::DenseBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >::CastXpr<NewType>::Type Eigen::DenseBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >::cast() const [with NewType = double]'
62 | cast() const
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:38: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t<stan::is_eigen_col_vector<T> >* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
102 | result << A.template cast<T_return>(), B;
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0);
| ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:5,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_2F1_converges.hpp:5,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err.hpp:4,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim.hpp:12:
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::Matrix<double, -1, 1> >(const char*, const char*, const Eigen::Matrix<double, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<double, -1, 1>]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:47:0: required from here
47 | stan::math::check_not_nan(function, "Mean vector", mu);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<double, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::Matrix<double, -1, -1> >(const char*, const char*, const Eigen::Matrix<double, -1, -1>&)::<lambda(double)>; T = Eigen::Matrix<double, -1, -1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<double, -1, -1>]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:74:0: required from here
74 | stan::math::check_not_nan(function, "Cholesky factor", L_chol);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:207:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::Index' {aka 'long long int'} [-Wsign-compare]
207 | for (size_t i = 0; i < x.rows(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:208:26: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::Index' {aka 'long long int'} [-Wsign-compare]
208 | for (size_t j = 0; j < x.cols(); j++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite<Eigen::Matrix<double, -1, 1> >(const char*, const char*, const Eigen::Matrix<double, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from 'void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<double, -1, 1>]'
29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | y, "finite");
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:21:0: required from here
21 | stan::math::check_finite("check_finite", "inv_metric", inv_metric);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<double, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive<Eigen::Matrix<double, -1, 1> >(const char*, const char*, const Eigen::Matrix<double, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from 'void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<double, -1, 1>]'
29 | elementwise_check([](double x) { return x > 0; }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | "positive");
| ~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:22:0: required from here
22 | stan::math::check_positive("check_positive", "inv_metric", inv_metric);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<double, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from 'bool Eigen::DenseBase<Derived>::hasNaN() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >]'
142 | return !((derived().array()==derived().array()).all());
| ~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from 'bool Eigen::DenseBase<Derived>::allFinite() const [with Derived = Eigen::Matrix<double, -1, -1>]'
156 | return !((derived()-derived()).hasNaN());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here
31 | if (!covar.allFinite())
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from 'bool Eigen::DenseBase<Derived>::hasNaN() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >]'
142 | return !((derived().array()==derived().array()).all());
| ~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from 'bool Eigen::DenseBase<Derived>::allFinite() const [with Derived = Eigen::Matrix<double, -1, 1>]'
156 | return !((derived()-derived()).hasNaN());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:30:0: required from here
30 | if (!var.allFinite())
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta.hpp:70,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/invalid_argument.hpp:4,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/core/init_threadpool_tbb.hpp:4,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/core.hpp:4,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim.hpp:10:
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp: In instantiation of 'void stan::math::check_less_or_equal(const char*, const char*, const T_y&, const T_high&, Idxs ...) [with T_y = long long unsigned int; T_high = long long int; stan::require_all_stan_scalar_t<U, V>* <anonymous> = 0; Idxs = {}]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp:79:0: required from 'std::vector<long long unsigned int> stan::io::array_var_context::validate_dims(const std::vector<std::__cxx11::basic_string<char> >&, T, const std::vector<std::vector<long long unsigned int> >&) [with T = long long int]'
79 | stan::math::check_less_or_equal("validate_dims", "array_var_context",
80 | elem_dims_total[dims.size()], array_size);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here
118 | std::vector<size_t> dim_vec = validate_dims(names, values.size(), dims);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp:39:20: warning: comparison of integer expressions of different signedness: 'const long long unsigned int' and 'const long long int' [-Wsign-compare]
39 | if (unlikely(!(y <= high))) {
| ~~~^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/compiler_attributes.hpp:9:41: note: in definition of macro 'unlikely'
9 | #define unlikely(x) __builtin_expect(!!(x), 0)
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:21: required from 'auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix<double, -1, 1>; Scal = int; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_all_not_st_var<Scal, Mat>* <anonymous> = 0]'
79 | return (m.array() - c).matrix();
| ~~~~~~~~~~~^~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:29: required from 'auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
37 | return eval(log(subtract(std::forward<decltype(y_ref)>(y_ref),
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | std::forward<decltype(lb_ref)>(lb_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer<T>::write_free_lb(const L&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; T = double]'
253 | this->write(stan::math::lb_free(x, lb));
stanExports_stanmarg.h:19873:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19873 | out__.write_free_lb(0, Theta_sd_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:32: required from 'auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix<double, -1, 1>; Scal = int; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_all_not_st_var<Scal, Mat>* <anonymous> = 0]'
79 | return (m.array() - c).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:29: required from 'auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
37 | return eval(log(subtract(std::forward<decltype(y_ref)>(y_ref),
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | std::forward<decltype(lb_ref)>(lb_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer<T>::write_free_lb(const L&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; T = double]'
253 | this->write(stan::math::lb_free(x, lb));
stanExports_stanmarg.h:19873:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19873 | out__.write_free_lb(0, Theta_sd_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from 'stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)> [with auto:169 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)>; T2 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >]'
47 | f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from 'auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
37 | return eval(log(subtract(std::forward<decltype(y_ref)>(y_ref),
| ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | std::forward<decltype(lb_ref)>(lb_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer<T>::write_free_lb(const L&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; T = double]'
253 | this->write(stan::math::lb_free(x, lb));
stanExports_stanmarg.h:19873:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19873 | out__.write_free_lb(0, Theta_sd_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)> [with auto:169 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)>; T2 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >]'
47 | f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from 'auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
37 | return eval(log(subtract(std::forward<decltype(y_ref)>(y_ref),
| ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | std::forward<decltype(lb_ref)>(lb_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer<T>::write_free_lb(const L&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; T = double]'
253 | this->write(stan::math::lb_free(x, lb));
stanExports_stanmarg.h:19873:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19873 | out__.write_free_lb(0, Theta_sd_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply<stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)> >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&, const stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)>&)::<lambda(const auto:6&)> [with auto:6 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply<stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)> >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&, const stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)>&)::<lambda(const auto:6&)>; Args = {Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1, 0, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1, 0, -1, 1> > > > > >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(const auto:169&)>; T2 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
47 | f(x));
| ~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lb_free.hpp:37:20: required from 'auto stan::math::lb_free(T&&, L&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
37 | return eval(log(subtract(std::forward<decltype(y_ref)>(y_ref),
| ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | std::forward<decltype(lb_ref)>(lb_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer<T>::write_free_lb(const L&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; T = double]'
253 | this->write(stan::math::lb_free(x, lb));
stanExports_stanmarg.h:19873:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19873 | out__.write_free_lb(0, Theta_sd_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:62:13: required from 'auto stan::math::subtract(Scal, const Mat&) [with Scal = int; Mat = Eigen::Matrix<double, -1, 1>; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Scal, Mat>* <anonymous> = 0]'
62 | return (c - m.array()).matrix();
| ~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:29: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix<double, -1, 1>; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
43 | return eval(log(subtract(std::forward<decltype(ub_ref)>(ub_ref),
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
44 | std::forward<decltype(y_ref)>(y_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:54:19: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
54 | return ub_free(identity_free(y, lb), ub);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:62:32: required from 'auto stan::math::subtract(Scal, const Mat&) [with Scal = int; Mat = Eigen::Matrix<double, -1, 1>; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Scal, Mat>* <anonymous> = 0]'
62 | return (c - m.array()).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:29: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix<double, -1, 1>; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
43 | return eval(log(subtract(std::forward<decltype(ub_ref)>(ub_ref),
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
44 | std::forward<decltype(y_ref)>(y_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:54:19: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
54 | return ub_free(identity_free(y, lb), ub);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from 'stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(const auto:169&)> [with auto:169 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(const auto:169&)>; T2 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >]'
47 | f(x));
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:20: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix<double, -1, 1>; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
43 | return eval(log(subtract(std::forward<decltype(ub_ref)>(ub_ref),
| ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
44 | std::forward<decltype(y_ref)>(y_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:54:19: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
54 | return ub_free(identity_free(y, lb), ub);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:20: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix<double, -1, 1>; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
43 | return eval(log(subtract(std::forward<decltype(ub_ref)>(ub_ref),
| ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
44 | std::forward<decltype(y_ref)>(y_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:54:19: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
54 | return ub_free(identity_free(y, lb), ub);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, void>::apply<stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(const auto:169&)> >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&, const stan::math::log<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(const auto:169&)>&)::<lambda(const auto:6&)> [with auto:6 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
65 | return apply_vector_unary<Container>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:20: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix<double, -1, 1>; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0]'
43 | return eval(log(subtract(std::forward<decltype(ub_ref)>(ub_ref),
| ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
44 | std::forward<decltype(y_ref)>(y_ref))));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:54:19: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
54 | return ub_free(identity_free(y, lb), ub);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:33: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; T2 = double; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:59:29: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
59 | return eval(logit(divide(subtract(std::forward<decltype(y_ref)>(y_ref), lb),
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
60 | subtract(ub, lb))));
| ~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:64: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; T2 = double; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:59:29: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
59 | return eval(logit(divide(subtract(std::forward<decltype(y_ref)>(y_ref), lb),
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
60 | subtract(ub, lb))));
| ~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/logit.hpp:113:51: required from 'stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>::<lambda(const auto:341&)> [with auto:341 = Eigen::Matrix<double, -1, 1>]'
113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/logit.hpp:109:21: required from 'auto stan::math::logit(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
109 | return make_holder(
| ~~~~~~~~~~~^
110 | [](const auto& v_ref) {
| ~~~~~~~~~~~~~~~~~~~~~~~
111 | return apply_vector_unary<ref_type_t<Container>>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | v_ref,
| ~~~~~~
113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
114 | },
| ~~
115 | to_ref(x));
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:59:22: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
59 | return eval(logit(divide(subtract(std::forward<decltype(y_ref)>(y_ref), lb),
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
60 | subtract(ub, lb))));
| ~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/logit.hpp:113:73: required from 'stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>::<lambda(const auto:341&)> [with auto:341 = Eigen::Matrix<double, -1, 1>]'
113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/logit.hpp:109:21: required from 'auto stan::math::logit(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
109 | return make_holder(
| ~~~~~~~~~~~^
110 | [](const auto& v_ref) {
| ~~~~~~~~~~~~~~~~~~~~~~~
111 | return apply_vector_unary<ref_type_t<Container>>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | v_ref,
| ~~~~~~
113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
114 | },
| ~~
115 | to_ref(x));
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:59:22: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
59 | return eval(logit(divide(subtract(std::forward<decltype(y_ref)>(y_ref), lb),
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
60 | subtract(ub, lb))));
| ~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary<Eigen::Matrix<double, -1, 1>, void>::apply<stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>::<lambda(const auto:341&)> >(const Eigen::Matrix<double, -1, 1>&, const stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>::<lambda(const auto:341&)>&)::<lambda(const auto:6&)> [with auto:6 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >]'
46 | return make_holder([](const auto& a) { return a.matrix().derived(); },
| ~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary<Eigen::Matrix<double, -1, 1>, void>::apply<stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>::<lambda(const auto:341&)> >(const Eigen::Matrix<double, -1, 1>&, const stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>::<lambda(const auto:341&)>&)::<lambda(const auto:6&)>; Args = {Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1, 0, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1, 0, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1, 0, -1, 1> > > > >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/logit.hpp:109:21: required from 'auto stan::math::logit(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
109 | return make_holder(
| ~~~~~~~~~~~^
110 | [](const auto& v_ref) {
| ~~~~~~~~~~~~~~~~~~~~~~~
111 | return apply_vector_unary<ref_type_t<Container>>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | v_ref,
| ~~~~~~
113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
114 | },
| ~~
115 | to_ref(x));
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:59:22: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
59 | return eval(logit(divide(subtract(std::forward<decltype(y_ref)>(y_ref), lb),
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
60 | subtract(ub, lb))));
| ~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<stan::math::Holder<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, Eigen::Matrix<double, -1, 1, 0, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<stan::math::Holder<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, Eigen::Matrix<double, -1, 1, 0, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<stan::math::Holder<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, Eigen::Matrix<double, -1, 1, 0, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from 'class stan::math::Holder<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, Eigen::Matrix<double, -1, 1, 0, -1, 1> >'
115 | class Holder
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:312:16: required from 'auto stan::math::internal::make_holder_impl_construct_object(T&&, std::index_sequence<Is ...>, const std::tuple<Args* ...>&) [with T = Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >; long long unsigned int ...Is = {0}; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>}; std::index_sequence<Is ...> = std::integer_sequence<long long unsigned int, 0>]'
312 | return holder(std::forward<T>(expr), std::get<Is>(ptrs)...);
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from 'auto stan::math::internal::make_holder_impl(const F&, std::index_sequence<Is ...>, Args&& ...) [with F = stan::math::logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>; long long unsigned int ...Is = {0}; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>}; std::index_sequence<Is ...> = std::integer_sequence<long long unsigned int, 0>]'
330 | return make_holder_impl_construct_object(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
331 | func(*std::get<Is>(res)...),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
332 | std::make_index_sequence<std::tuple_size<decltype(ptrs)>::value>(), ptrs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:353:36: required from 'auto stan::math::make_holder(const F&, Args&& ...) [with F = logit<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(const auto:340&)>; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>}; stan::require_not_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = 0]'
353 | return internal::make_holder_impl(func,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~
354 | std::make_index_sequence<sizeof...(Args)>(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
355 | std::forward<Args>(args)...);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/logit.hpp:109:21: required from 'auto stan::math::logit(const Container&) [with Container = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
109 | return make_holder(
| ~~~~~~~~~~~^
110 | [](const auto& v_ref) {
| ~~~~~~~~~~~~~~~~~~~~~~~
111 | return apply_vector_unary<ref_type_t<Container>>::apply(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | v_ref,
| ~~~~~~
113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
114 | },
| ~~
115 | to_ref(x));
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/lub_free.hpp:59:22: required from 'auto stan::math::lub_free(T&&, L&&, U&&) [with T = const Eigen::Matrix<double, -1, 1>&; L = const int&; U = const int&; stan::require_not_std_vector_t<T_y>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0]'
59 | return eval(logit(divide(subtract(std::forward<decltype(y_ref)>(y_ref), lb),
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
60 | subtract(ub, lb))));
| ~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer<T>::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix<double, -1, 1>; L = int; U = int; T = double]'
281 | this->write(stan::math::lub_free(x, lb, ub));
stanExports_stanmarg.h:19892:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19892 | out__.write_free_lub(-1, 1, Theta_r_free);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp: In instantiation of 'int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]':
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1253:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::standalone_gqs(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1253 | ret = stan::services::standalone_generate(model_, draws,
1254 | Rcpp::as<unsigned int>(seed), interrupt, logger, *sample_writer_ptr);
stanExports_stanmarg.cc:30:0: required from here
30 | .method("standalone_gqs", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::standalone_gqs)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:55: warning: comparison of integer expressions of different signedness: 'std::vector<std::__cxx11::basic_string<char> >::size_type' {aka 'long long unsigned int'} and 'Eigen::Index' {aka 'long long int'} [-Wsign-compare]
55 | if (p_names.size() != draws.cols()) {
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:71: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::Index' {aka 'long long int'} [-Wsign-compare]
71 | for (size_t i = 0; i < draws.rows(); ++i) {
In file included from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/assert.hpp:35,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:20,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:19,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/size_type.hpp:20,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/size.hpp:21,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/functions.hpp:20,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range.hpp:18,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/numeric/odeint/util/resize.hpp:24:
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::constraint<Model>::failed() [with Model = boost::algorithm::FinderConcept<boost::algorithm::detail::token_finderF<boost::algorithm::detail::is_any_ofF<char> >, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:81:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:65:52: warning: 'this' pointer is null [-Wnonnull]
65 | static void failed() { ((Model*)0)->constraints(); }
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
In file included from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:26,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:16,
from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string.hpp:23,
from D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:4,
from D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:46:
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function 'void boost::algorithm::FinderConcept<FinderT, IteratorT>::constraints() [with FinderT = boost::algorithm::detail::token_finderF<boost::algorithm::detail::is_any_ofF<char> >; IteratorT = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]'
40 | void constraints()
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::constraint<Model>::failed() [with Model = boost::algorithm::FinderConcept<boost::algorithm::detail::first_finderF<const char*, boost::algorithm::is_equal>, __gnu_cxx::__normal_iterator<const char*, std::__cxx11::basic_string<char> > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/find_format.hpp:98:0: required from 'void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string<char>; FinderT = detail::first_finderF<const char*, is_equal>; FormatterT = detail::const_formatF<boost::iterator_range<const char*> >]'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/replace.hpp:179:0: required from 'void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string<char>; Range1T = char [11]; Range2T = char [1]]'
179 | ::boost::algorithm::find_format(
180 | Input,
181 | ::boost::algorithm::first_finder(Search),
182 | ::boost::algorithm::const_formatter(Format) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here
133 | boost::replace_first(value, " (Default)", "");
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:65:52: warning: 'this' pointer is null [-Wnonnull]
65 | static void failed() { ((Model*)0)->constraints(); }
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function 'void boost::algorithm::FinderConcept<FinderT, IteratorT>::constraints() [with FinderT = boost::algorithm::detail::first_finderF<const char*, boost::algorithm::is_equal>; IteratorT = __gnu_cxx::__normal_iterator<const char*, std::__cxx11::basic_string<char> >]'
40 | void constraints()
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::constraint<Model>::failed() [with Model = boost::algorithm::FormatterConcept<boost::algorithm::detail::const_formatF<boost::iterator_range<const char*> >, boost::algorithm::detail::first_finderF<const char*, boost::algorithm::is_equal>, __gnu_cxx::__normal_iterator<const char*, std::__cxx11::basic_string<char> > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/find_format.hpp:103:0: required from 'void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string<char>; FinderT = detail::first_finderF<const char*, is_equal>; FormatterT = detail::const_formatF<boost::iterator_range<const char*> >]'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/replace.hpp:179:0: required from 'void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string<char>; Range1T = char [11]; Range2T = char [1]]'
179 | ::boost::algorithm::find_format(
180 | Input,
181 | ::boost::algorithm::first_finder(Search),
182 | ::boost::algorithm::const_formatter(Format) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here
133 | boost::replace_first(value, " (Default)", "");
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:65:52: warning: 'this' pointer is null [-Wnonnull]
65 | static void failed() { ((Model*)0)->constraints(); }
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/concept.hpp:65: note: in a call to non-static member function 'void boost::algorithm::FormatterConcept<FormatterT, FinderT, IteratorT>::constraints() [with FormatterT = boost::algorithm::detail::const_formatF<boost::iterator_range<const char*> >; FinderT = boost::algorithm::detail::first_finderF<const char*, boost::algorithm::is_equal>; IteratorT = __gnu_cxx::__normal_iterator<const char*, std::__cxx11::basic_string<char> >]'
65 | void constraints()
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:112:44: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_L(const T&, size_t, stan::value_type_t<T>&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
112 | const Eigen::Ref<const plain_type_t<T>>& CPCs_ref = CPCs;
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:55: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t<T>&) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:62:47: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_L(const T&, size_t) [with T = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int]'
62 | acc.tail(pull) = T_scalar(1.0) - temp.square();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:32:55: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int]'
32 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:45:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int]'
45 | return read_corr_matrix(corr_constrain(x), k);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:949:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
949 | return corr_matrix_constrain(
950 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
951 | k);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:62:34: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_L(const T&, size_t) [with T = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int]'
62 | acc.tail(pull) = T_scalar(1.0) - temp.square();
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:32:55: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int]'
32 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:45:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int]'
45 | return read_corr_matrix(corr_constrain(x), k);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:949:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
949 | return corr_matrix_constrain(
950 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
951 | k);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:68:32: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_L(const T&, size_t) [with T = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int]'
68 | L.col(i).tail(pull) = temp * acc.tail(pull).sqrt();
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:32:55: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int]'
32 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:45:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int]'
45 | return read_corr_matrix(corr_constrain(x), k);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:949:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
949 | return corr_matrix_constrain(
950 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
951 | k);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_exp_op<double>, const Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58: required from 'stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]'
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]'
93 | return f(x);
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from 'auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]'
83 | return apply_vector_unary<T>::reduce(x, [&](const auto& v) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
84 | if (v.size() == 0) {
| ~~~~~~~~~~~~~~~~~~~~
85 | return NEGATIVE_INFTY;
| ~~~~~~~~~~~~~~~~~~~~~~
86 | }
| ~
87 | const auto& v_ref = to_ref(v);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
88 | const double max = v_ref.maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
89 | if (!std::isfinite(max)) {
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
90 | return max;
| ~~~~~~~~~~~
91 | }
| ~
92 | return max + std::log((v_ref.array() - max).exp().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
93 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here
59 | double log_sum_y = log_sum_exp(log_y);
| ~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:330:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'class Eigen::internal::gebp_traits<double, double, false, false, 1, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:72:102: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
72 | typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor, Unaligned, ResInnerStride> ResMapper;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable,
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable,
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
460 | typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
461 | typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
462 | typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
465 | typedef QuadPacket<RhsPacket> RhsPacketx4;
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'class Eigen::internal::gebp_traits<double, double, false, false, 1, 1>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1080:42: required from 'struct Eigen::internal::gebp_kernel<double, double, long long int, Eigen::internal::blas_data_mapper<double, long long int, 0, 0, 1>, 4, 4, false, false>'
1080 | typedef typename HalfTraits::LhsPacket LhsPacketHalf;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
92 | gebp_kernel<LhsScalar, RhsScalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable,
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable,
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
460 | typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
461 | typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
462 | typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
465 | typedef QuadPacket<RhsPacket> RhsPacketx4;
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'class Eigen::internal::gebp_traits<double, double, false, false, 1, 2>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1085:45: required from 'struct Eigen::internal::gebp_kernel<double, double, long long int, Eigen::internal::blas_data_mapper<double, long long int, 0, 0, 1>, 4, 4, false, false>'
1085 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
92 | gebp_kernel<LhsScalar, RhsScalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
384 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable,
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable,
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
460 | typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
461 | typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
462 | typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
465 | typedef QuadPacket<RhsPacket> RhsPacketx4;
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from 'Eigen::CommaInitializer<Derived> Eigen::DenseBase<Derived>::operator<<(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix<double, -1, 1>]'
159 | return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t<stan::is_eigen_col_vector<T> >* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
102 | result << A.template cast<T_return>(), B;
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0);
| ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::Matrix<double, -1, 1>; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix<double, -1, 1>; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::Matrix<double, -1, 1> >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:478:32: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::mean() const [with Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
478 | return Scalar(derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>())) / Scalar(this->size());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here
25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean();
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:451:40: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
451 | subdiag = mat.template diagonal<-1>().real();
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:91: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
| ~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, -1>'
56 | template<typename VectorType, int Size> class VectorBlock
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:101: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
| ~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:126:21: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_L(const T&, size_t, stan::value_type_t<T>&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
126 | return read_corr_L(CPCs_ref, K);
| ~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:55: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t<T>&) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:46: required from 'stan::math::matrix_d stan::math::multiply_lower_tri_self_transpose(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_matrix_dynamic_t<EigMat>* <anonymous> = 0; stan::require_not_st_autodiff<EigMat>* <anonymous> = 0; matrix_d = Eigen::Matrix<double, -1, -1>]'
35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t<T>&) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:191:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
191 | _pk.noalias() = -_gk;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:192:0: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]'
192 | auto exp_x = to_arena(arena_x.val().array().exp());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, int>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:193:0: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]'
193 | arena_t<ret_type> ret = exp_x + lb_val;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:197:0: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]'
197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:197:0: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]'
197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)> [with auto:11 = const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]'
213 | arena_t<ret_type> ret = value_of(x_ref).array().exp() + lb_val;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]'
213 | arena_t<ret_type> ret = value_of(x_ref).array().exp() + lb_val;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]'
213 | arena_t<ret_type> ret = value_of(x_ref).array().exp() + lb_val;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer<T>::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
386 | return stan::math::lb_constrain(this->read<Ret>(sizes...), lb, lp);
stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12962 | Theta_sd_free = in__.template read_constrain_lb<
12963 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(0,
12964 | lp__, Theta_sd_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: required from 'auto stan::math::lb_constrain(const T&, const L&, stan::return_type_t<T1, T2>&) [with T = Eigen::Matrix<var_value<double>, -1, 1>; L = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]'
213 | arena_t<ret_type> ret = value_of(x_ref).array().exp() + lb_val;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:209:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
209 | return ret_type(lb_constrain(identity_constrain(x, ub), lb, lp));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lb_constrain.hpp:213:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/ub_constrain.hpp:195:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/ub_constrain.hpp:196:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/ub_constrain.hpp:215:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/ub_constrain.hpp:215:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)> [with auto:11 = stan::math::arena_matrix<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:215:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
215 | auto neg_abs_x = to_arena(-(value_of(arena_x).array()).abs());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:215:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
215 | auto neg_abs_x = to_arena(-(value_of(arena_x).array()).abs());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:215:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
215 | auto neg_abs_x = to_arena(-(value_of(arena_x).array()).abs());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_exp_fun; T = stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:217:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
217 | lp += (log(diff) + (neg_abs_x - (2.0 * log1p_exp(neg_abs_x)))).sum();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:217:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
217 | lp += (log(diff) + (neg_abs_x - (2.0 * log1p_exp(neg_abs_x)))).sum();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_exp_fun, stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>, void>::apply(const stan::math::arena_matrix<Eigen::Array<double, -1, 1>, void>&)::<lambda(auto:3&&)>, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:217:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
217 | lp += (log(diff) + (neg_abs_x - (2.0 * log1p_exp(neg_abs_x)))).sum();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:219:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
219 | arena_t<ret_type> ret = diff * inv_logit_x + lb_val;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:219:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
219 | arena_t<ret_type> ret = diff * inv_logit_x + lb_val;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:224:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:224:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:224:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:224:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:225:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
225 | + lp.adj() * (1.0 - 2.0 * inv_logit_x);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:225:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
225 | + lp.adj() * (1.0 - 2.0 * inv_logit_x);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:225:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
225 | + lp.adj() * (1.0 - 2.0 * inv_logit_x);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:225:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x)
225 | + lp.adj() * (1.0 - 2.0 * inv_logit_x);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/lub_constrain.hpp:231:0: required from 'auto stan::math::lub_constrain(const T&, const L&, const U&, stan::return_type_t<T_x, T_sigma, T_l>&) [with T = Eigen::Map<const Eigen::Matrix<var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t<T>* <anonymous> = 0; stan::require_all_stan_scalar_t<L, U>* <anonymous> = 0; stan::require_var_t<typename stan::return_type<T_x, T_sigma, T_l>::type>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = var_value<double>]'
231 | += (ret.adj().array() * (1.0 - inv_logit_x)).sum()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
441 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub, lp);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/ub_constrain.hpp:163:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:443:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
443 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:443:0: required from 'auto stan::io::deserializer<T>::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value<double>; Sizes = {int}; T = stan::math::var_value<double>]'
443 | return stan::math::lub_constrain(this->read<Ret>(sizes...), lb, ub);
stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12969 | Theta_r_free = in__.template read_constrain_lub<
12970 | Eigen::Matrix<local_scalar_t__,-1,1>, jacobian__>(-1,
12971 | 1, lp__, Theta_r_free_1dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:113:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
113 | using op_ret_type = decltype(a.val() + b.val());
stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:113:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
113 | using op_ret_type = decltype(a.val() + b.val());
stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> > > >, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> > >'
80 | : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >::val_Op, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> >}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:114:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
114 | using ret_type = return_var_matrix_t<op_ret_type, VarMat1, VarMat2>;
stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
117 | arena_t<ret_type> ret(arena_a.val() + arena_b.val());
stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
117 | arena_t<ret_type> ret(arena_a.val() + arena_b.val());
stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
117 | arena_t<ret_type> ret(arena_a.val() + arena_b.val());
stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:123:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
123 | arena_b.adj().coeffRef(i, j) += ref_adj;
stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:154:0: required from 'auto stan::math::subtract(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
154 | (a.val().array() - as_array_or_scalar(b)).matrix())>;
stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13360 | stan::math::subtract(
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
13367 | stan::math::diag_matrix(stan::math::rep_vector(1, p))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:154:0: required from 'auto stan::math::subtract(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
154 | (a.val().array() - as_array_or_scalar(b)).matrix())>;
stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13360 | stan::math::subtract(
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
13367 | stan::math::diag_matrix(stan::math::rep_vector(1, p))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template<class T> struct stan::plain_type<T, typename std::enable_if<stan::math::conjunction<stan::is_var<T, void>, stan::is_eigen<typename stan::value_type<T, void>::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >]'
22 | using plain_type_t = typename plain_type<T>::type;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template<class T> using stan::plain_type_t = typename stan::plain_type<T>::type [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >]'
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:153:0: required from 'auto stan::math::subtract(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
153 | using op_ret_type = plain_type_t<decltype(
stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13360 | stan::math::subtract(
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
13367 | stan::math::diag_matrix(stan::math::rep_vector(1, p))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:157:0: required from 'auto stan::math::subtract(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
157 | arena_t<ret_type> ret(arena_a.val().array() - as_array_or_scalar(b));
stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13360 | stan::math::subtract(
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
13367 | stan::math::diag_matrix(stan::math::rep_vector(1, p))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:157:0: required from 'auto stan::math::subtract(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
157 | arena_t<ret_type> ret(arena_a.val().array() - as_array_or_scalar(b));
stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13360 | stan::math::subtract(
13361 | stan::math::add(
13362 | stan::model::rvalue(T_r_lower, "T_r_lower",
13363 | stan::model::index_uni(g)),
13364 | stan::math::transpose(
13365 | stan::model::rvalue(T_r_lower, "T_r_lower",
13366 | stan::model::index_uni(g)))),
13367 | stan::math::diag_matrix(stan::math::rep_vector(1, p))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:13&)> [with auto:13 = const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
180 | (as_array_or_scalar(a) - b.val().array()).matrix())>;
stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13574 | stan::math::subtract(I,
13575 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
180 | (as_array_or_scalar(a) - b.val().array()).matrix())>;
stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13574 | stan::math::subtract(I,
13575 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template<class T> struct stan::plain_type<T, typename std::enable_if<stan::math::conjunction<stan::is_var<T, void>, stan::is_eigen<typename stan::value_type<T, void>::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > >]'
22 | using plain_type_t = typename plain_type<T>::type;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template<class T> using stan::plain_type_t = typename stan::plain_type<T>::type [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > > >]'
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:179:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
179 | using op_ret_type = plain_type_t<decltype(
stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13574 | stan::math::subtract(I,
13575 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:183:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
183 | arena_t<ret_type> ret(as_array_or_scalar(a) - arena_b.val().array());
stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13574 | stan::math::subtract(I,
13575 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:185:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
185 | [ret, arena_b]() mutable { arena_b.adj() -= ret.adj_op(); });
stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13574 | stan::math::subtract(I,
13575 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> > >, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> >'
80 | : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:114:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
114 | using ret_type = return_var_matrix_t<op_ret_type, VarMat1, VarMat2>;
stanExports_stanmarg.h:13615:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13615 | stan::math::add(
13616 | stan::model::deep_copy(
13617 | stan::model::rvalue(Sigma, "Sigma",
13618 | stan::model::index_uni(g),
13619 | stan::model::index_min_max(1, p),
13620 | stan::model::index_min_max(1, p))),
13621 | stan::math::quad_form_sym(
13622 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
13623 | stan::math::transpose(
13624 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13625 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
117 | arena_t<ret_type> ret(arena_a.val() + arena_b.val());
stanExports_stanmarg.h:13615:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13615 | stan::math::add(
13616 | stan::model::deep_copy(
13617 | stan::model::rvalue(Sigma, "Sigma",
13618 | stan::model::index_uni(g),
13619 | stan::model::index_min_max(1, p),
13620 | stan::model::index_min_max(1, p))),
13621 | stan::math::quad_form_sym(
13622 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
13623 | stan::math::transpose(
13624 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13625 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix<const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, -1, 1, true>, -1> >'
80 | : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, -1, 1, true>, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
36 | using return_t
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:47:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
47 | arena_A.adj() += res_adj * arena_B_val.transpose();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
48 | arena_B.adj() += arena_A_val.transpose() * res_adj;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)> [with auto:11 = const Eigen::Matrix<stan::math::var_value<double>, -1, -1>]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:53:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
53 | arena_t<promote_scalar_t<double, T1>> arena_A = value_of(A);
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, 1, true>, -1, 1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>&)::<lambda(auto:11&)> [with auto:11 = const Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, 1, true>, -1>]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:56:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
56 | = return_var_matrix_t<decltype(arena_A * value_of(B).eval()), T1, T2>;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix<const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, -1, 1, true>, -1> >'
80 | : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, -1, 1, true>, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
55 | using return_t
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
57 | arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
57 | arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:11&)> [with auto:11 = stan::math::arena_matrix<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, void>]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:66:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
66 | = return_var_matrix_t<decltype(value_of(arena_A).eval() * arena_B), T1,
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix<const Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, -1, 1, true>, -1> >'
80 | : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, -1, 1, true>, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
65 | using return_t
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
68 | arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
68 | arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:113:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, 1>; VarMat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
113 | using op_ret_type = decltype(a.val() + b.val());
stanExports_stanmarg.h:13633:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13633 | stan::math::add(
13634 | stan::model::deep_copy(
13635 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(g),
13636 | stan::model::index_min_max(1, p))),
13637 | stan::math::to_vector(
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> > >, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >'
80 | : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:114:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, 1>; VarMat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
114 | using ret_type = return_var_matrix_t<op_ret_type, VarMat1, VarMat2>;
stanExports_stanmarg.h:13633:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13633 | stan::math::add(
13634 | stan::model::deep_copy(
13635 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(g),
13636 | stan::model::index_min_max(1, p))),
13637 | stan::math::to_vector(
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from 'auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, 1>; VarMat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
117 | arena_t<ret_type> ret(arena_a.val() + arena_b.val());
stanExports_stanmarg.h:13633:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13633 | stan::math::add(
13634 | stan::model::deep_copy(
13635 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(g),
13636 | stan::model::index_min_max(1, p))),
13637 | stan::math::to_vector(
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = int; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from 'auto stan::math::add(const Arith&, const VarMat&) [with Arith = int; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
169 | return add(b, a);
stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = int; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from 'auto stan::math::add(const Arith&, const VarMat&) [with Arith = int; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
169 | return add(b, a);
stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
29 | = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::value
| ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = int; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
148 | using ret_type = return_var_matrix_t<op_ret_type, VarMat>;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from 'auto stan::math::add(const Arith&, const VarMat&) [with Arith = int; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
169 | return add(b, a);
stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, int>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = int; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
150 | arena_t<ret_type> ret(arena_a.val().array() + as_array_or_scalar(b));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from 'auto stan::math::add(const Arith&, const VarMat&) [with Arith = int; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
169 | return add(b, a);
stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:145:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
145 | arena_t<return_t> res = arena_A.val() * arena_B.val().array();
stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:163:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
163 | arena_B.adj().array() += arena_A * res.adj().array();
stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:170:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
170 | arena_t<return_t> res = arena_A.val() * arena_B.array();
stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:170:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
170 | arena_t<return_t> res = arena_A.val() * arena_B.array();
stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:172:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
172 | arena_A.adj() += (res.adj().array() * arena_B.array()).sum();
stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:40:13: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~~~
40 | .solve(Eigen::Matrix<T_return, Eigen::Dynamic, Eigen::Dynamic>(b)
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
41 | .transpose())
| ~~~~~~~~~~~~~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~~~
40 | .solve(Eigen::Matrix<T_return, Eigen::Dynamic, Eigen::Dynamic>(b)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
41 | .transpose())
| ~~~~~~~~~~~~~
42 | .transpose();
| ~~~~~~~~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:26: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:34: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:36:40: required from 'stan::math::quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:377&)> [with auto:377 = Eigen::Matrix<double, -1, -1>]'
36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); },
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:377&)>; Args = {const Eigen::Matrix<double, -1, -1, 0, -1, -1>}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
35 | return make_holder(
| ~~~~~~~~~~~^
36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); },
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<stan::math::Holder<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, const Eigen::Matrix<double, -1, -1, 0, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<stan::math::Holder<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, const Eigen::Matrix<double, -1, -1, 0, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<stan::math::Holder<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, const Eigen::Matrix<double, -1, -1, 0, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from 'class stan::math::Holder<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, const Eigen::Matrix<double, -1, -1, 0, -1, -1> >'
115 | class Holder
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:312:16: required from 'auto stan::math::internal::make_holder_impl_construct_object(T&&, std::index_sequence<Is ...>, const std::tuple<Args* ...>&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >; long long unsigned int ...Is = {0}; Args = {const Eigen::Matrix<double, -1, -1, 0, -1, -1>}; std::index_sequence<Is ...> = std::integer_sequence<long long unsigned int, 0>]'
312 | return holder(std::forward<T>(expr), std::get<Is>(ptrs)...);
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from 'auto stan::math::internal::make_holder_impl(const F&, std::index_sequence<Is ...>, Args&& ...) [with F = stan::math::quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:377&)>; long long unsigned int ...Is = {0}; Args = {const Eigen::Matrix<double, -1, -1, 0, -1, -1>}; std::index_sequence<Is ...> = std::integer_sequence<long long unsigned int, 0>]'
330 | return make_holder_impl_construct_object(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
331 | func(*std::get<Is>(res)...),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
332 | std::make_index_sequence<std::tuple_size<decltype(ptrs)>::value>(), ptrs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:353:36: required from 'auto stan::math::make_holder(const F&, Args&& ...) [with F = quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:377&)>; Args = {const Eigen::Matrix<double, -1, -1, 0, -1, -1>}; stan::require_not_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = 0]'
353 | return internal::make_holder_impl(func,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~
354 | std::make_index_sequence<sizeof...(Args)>(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
355 | std::forward<Args>(args)...);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
35 | return make_holder(
| ~~~~~~~~~~~^
36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); },
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:26: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:34: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:36:47: required from 'stan::math::quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >&)::<lambda(const auto:377&)> [with auto:377 = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); },
| ~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >&)::<lambda(const auto:377&)>; Args = {const Eigen::Matrix<double, -1, -1, 1, -1, -1>}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
35 | return make_holder(
| ~~~~~~~~~~~^
36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); },
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:36:40: required from 'stan::math::quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >&)::<lambda(const auto:377&)> [with auto:377 = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); },
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >&)::<lambda(const auto:377&)>; Args = {const Eigen::Matrix<double, -1, -1, 1, -1, -1>}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
35 | return make_holder(
| ~~~~~~~~~~~^
36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); },
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<stan::math::Holder<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<stan::math::Holder<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<stan::math::Holder<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from 'class stan::math::Holder<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
115 | class Holder
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:312:16: required from 'auto stan::math::internal::make_holder_impl_construct_object(T&&, std::index_sequence<Is ...>, const std::tuple<Args* ...>&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >; long long unsigned int ...Is = {0}; Args = {const Eigen::Matrix<double, -1, -1, 1, -1, -1>}; std::index_sequence<Is ...> = std::integer_sequence<long long unsigned int, 0>]'
312 | return holder(std::forward<T>(expr), std::get<Is>(ptrs)...);
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from 'auto stan::math::internal::make_holder_impl(const F&, std::index_sequence<Is ...>, Args&& ...) [with F = stan::math::quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >&)::<lambda(const auto:377&)>; long long unsigned int ...Is = {0}; Args = {const Eigen::Matrix<double, -1, -1, 1, -1, -1>}; std::index_sequence<Is ...> = std::integer_sequence<long long unsigned int, 0>]'
330 | return make_holder_impl_construct_object(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
331 | func(*std::get<Is>(res)...),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
332 | std::make_index_sequence<std::tuple_size<decltype(ptrs)>::value>(), ptrs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:353:36: required from 'auto stan::math::make_holder(const F&, Args&& ...) [with F = quad_form_sym<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >(const Eigen::Matrix<double, -1, -1>&, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >&)::<lambda(const auto:377&)>; Args = {const Eigen::Matrix<double, -1, -1, 1, -1, -1>}; stan::require_not_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = 0]'
353 | return internal::make_holder_impl(func,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~
354 | std::make_index_sequence<sizeof...(Args)>(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
355 | std::forward<Args>(args)...);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
35 | return make_holder(
| ~~~~~~~~~~~^
36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); },
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: required from 'class Eigen::RefBase<Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
59 | template<typename Derived> class RefBase
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:329:77: required from 'class Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >'
329 | template<typename TPlainObjectType, int Options, typename StrideType> class Ref<const TPlainObjectType, Options, StrideType>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:31:49: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; typename stan::value_type<T>::type = double]'
31 | const Eigen::Ref<const plain_type_t<EigMat>>& m_ref = m;
| ^~~~~
stanExports_stanmarg.h:16304:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16304 | stan::math::inverse_spd(
16305 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:33:60: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; typename stan::value_type<T>::type = double]'
33 | plain_type_t<EigMat> mmt = 0.5 * (m_ref + m_ref.transpose());
| ~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16304:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16304 | stan::math::inverse_spd(
16305 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:33:43: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; typename stan::value_type<T>::type = double]'
33 | plain_type_t<EigMat> mmt = 0.5 * (m_ref + m_ref.transpose());
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:16304:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16304 | stan::math::inverse_spd(
16305 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Transpose<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:33:34: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; typename stan::value_type<T>::type = double]'
33 | plain_type_t<EigMat> mmt = 0.5 * (m_ref + m_ref.transpose());
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:16304:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16304 | stan::math::inverse_spd(
16305 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:44:20: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; typename stan::value_type<T>::type = double]'
44 | return ldlt.solve(
| ~~~~~~~~~~^
45 | Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>::Identity(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
46 | m.rows(), m.cols()));
| ~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:16304:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16304 | stan::math::inverse_spd(
16305 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:4436:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_cholesky_rng.hpp:72:55: required from 'typename stan::StdVectorBuilder<true, Eigen::Matrix<double, -1, 1>, T_loc>::type stan::math::multi_normal_cholesky_rng(const T_loc&, const Eigen::Matrix<double, -1, -1>&, RNG&) [with T_loc = Eigen::Matrix<double, -1, 1>; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; typename stan::StdVectorBuilder<true, Eigen::Matrix<double, -1, 1>, T_loc>::type = Eigen::Matrix<double, -1, 1>]'
72 | output[n] = as_column_vector_or_scalar(mu_vec[n]) + L_ref * z;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~
stanExports_stanmarg.h:17222:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17222 | stan::math::multi_normal_cholesky_rng(
17223 | stan::model::rvalue(Mu_c, "Mu_c",
17224 | stan::model::index_uni(gg)), Sigma_c_chol, base_rng__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: required from 'struct Eigen::internal::cast_return_type<Eigen::Matrix<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, 1> > >'
513 | typedef typename _CastType::Scalar NewScalarType;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/plugins/CommonCwiseUnaryOps.h:48:179: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/append_col.hpp:49:53: required from 'auto stan::math::append_col(const T1&, const T2&) [with T1 = Eigen::Matrix<double, -1, 1>; T2 = Eigen::Matrix<double, -1, -1>; <template-parameter-1-3> = void]'
49 | result.leftCols(Acols) = A.template cast<T_return>();
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:2847:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type>::type, -1, -1> model_stanmarg_namespace::calc_B_tilde(const T0__&, const T1__&, const std::vector<int>&, const int&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T1__ = Eigen::Matrix<double, -1, 1>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type>::type = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; std::ostream = std::basic_ostream<char>]'
2847 | stan::model::assign(out, stan::math::append_col(mu2, sig2),
stanExports_stanmarg.h:17229:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17229 | calc_B_tilde(
17230 | stan::model::rvalue(Sigma_c, "Sigma_c",
17231 | stan::model::index_uni(gg)), YXstar_rep_c, ov_idx2,
17232 | p_tilde, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: required from 'struct Eigen::internal::cast_return_type<Eigen::Matrix<double, -1, -1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Matrix<double, -1, -1> > >'
513 | typedef typename _CastType::Scalar NewScalarType;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/plugins/CommonCwiseUnaryOps.h:48:179: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/append_col.hpp:50:54: required from 'auto stan::math::append_col(const T1&, const T2&) [with T1 = Eigen::Matrix<double, -1, 1>; T2 = Eigen::Matrix<double, -1, -1>; <template-parameter-1-3> = void]'
50 | result.rightCols(Bcols) = B.template cast<T_return>();
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:2847:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type>::type, -1, -1> model_stanmarg_namespace::calc_B_tilde(const T0__&, const T1__&, const std::vector<int>&, const int&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T1__ = Eigen::Matrix<double, -1, 1>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type>::type = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; std::ostream = std::basic_ostream<char>]'
2847 | stan::model::assign(out, stan::math::append_col(mu2, sig2),
stanExports_stanmarg.h:17229:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17229 | calc_B_tilde(
17230 | stan::model::rvalue(Sigma_c, "Sigma_c",
17231 | stan::model::index_uni(gg)), YXstar_rep_c, ov_idx2,
17232 | p_tilde, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, 1>; Mat2 = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:4576:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2>::type, -1, 1> > model_stanmarg_namespace::calc_mean_vecs(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2>::type = double; std::ostream = std::basic_ostream<char>]'
4576 | stan::math::add(stan::model::deep_copy(ov_mean),
4577 | stan::model::rvalue(YXstar, "YXstar", stan::model::index_uni(i),
4578 | stan::model::index_multi(
4579 | stan::model::rvalue(Xvar, "Xvar",
4580 | stan::model::index_min_max(1, Nx))))),
stanExports_stanmarg.h:17686:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17686 | calc_mean_vecs(
17687 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17688 | stan::model::index_min_max(rr1, (r1 - 1))),
17689 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17690 | stan::model::index_min_max(r2, (clusidx - 1))),
17691 | stan::model::rvalue(nclus, "nclus",
17692 | stan::model::index_uni(gg)),
17693 | stan::model::rvalue(Xvar, "Xvar",
17694 | stan::model::index_uni(gg)),
17695 | stan::model::rvalue(Xbetvar, "Xbetvar",
17696 | stan::model::index_uni(gg)),
17697 | stan::model::rvalue(Nx, "Nx",
17698 | stan::model::index_uni(gg)),
17699 | stan::model::rvalue(Nx_between, "Nx_between",
17700 | stan::model::index_uni(gg)), p_tilde, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, 1>; Mat2 = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:4600:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2>::type, -1, 1> > model_stanmarg_namespace::calc_mean_vecs(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2>::type = double; std::ostream = std::basic_ostream<char>]'
4600 | stan::math::add(stan::model::deep_copy(ov_mean_d),
4601 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4602 | stan::model::index_min_max(1, Nx_between))),
stanExports_stanmarg.h:17686:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17686 | calc_mean_vecs(
17687 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17688 | stan::model::index_min_max(rr1, (r1 - 1))),
17689 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17690 | stan::model::index_min_max(r2, (clusidx - 1))),
17691 | stan::model::rvalue(nclus, "nclus",
17692 | stan::model::index_uni(gg)),
17693 | stan::model::rvalue(Xvar, "Xvar",
17694 | stan::model::index_uni(gg)),
17695 | stan::model::rvalue(Xbetvar, "Xbetvar",
17696 | stan::model::index_uni(gg)),
17697 | stan::model::rvalue(Nx, "Nx",
17698 | stan::model::index_uni(gg)),
17699 | stan::model::rvalue(Nx_between, "Nx_between",
17700 | stan::model::index_uni(gg)), p_tilde, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:4696:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::calc_cov_mats(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4696 | stan::math::subtract(
4697 | stan::model::rvalue(YXstar, "YXstar",
4698 | stan::model::index_uni(i),
4699 | stan::model::index_multi(
4700 | stan::model::rvalue(Xvar, "Xvar",
4701 | stan::model::index_min_max(1, Nx)))),
4702 | stan::model::rvalue(mean_vecs, "mean_vecs",
4703 | stan::model::index_uni(1),
4704 | stan::model::index_min_max(1, Nx)))))),
stanExports_stanmarg.h:17704:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17704 | calc_cov_mats(
17705 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17706 | stan::model::index_min_max(rr1, (r1 - 1))),
17707 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17708 | stan::model::index_min_max(r2, (clusidx - 1))),
17709 | mnvecs,
17710 | stan::model::rvalue(nclus, "nclus",
17711 | stan::model::index_uni(gg)),
17712 | stan::model::rvalue(Xvar, "Xvar",
17713 | stan::model::index_uni(gg)),
17714 | stan::model::rvalue(Xbetvar, "Xbetvar",
17715 | stan::model::index_uni(gg)),
17716 | stan::model::rvalue(Nx, "Nx",
17717 | stan::model::index_uni(gg)),
17718 | stan::model::rvalue(Nx_between, "Nx_between",
17719 | stan::model::index_uni(gg)), p_tilde, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; Mat2 = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:4740:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::calc_cov_mats(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4740 | stan::math::subtract(
4741 | stan::model::rvalue(mean_d, "mean_d",
4742 | stan::model::index_uni(cc),
4743 | stan::model::index_min_max(1, Nx_between)),
4744 | stan::model::rvalue(mean_vecs, "mean_vecs",
4745 | stan::model::index_uni(2),
4746 | stan::model::index_min_max(1, Nx_between)))))),
stanExports_stanmarg.h:17704:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17704 | calc_cov_mats(
17705 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17706 | stan::model::index_min_max(rr1, (r1 - 1))),
17707 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17708 | stan::model::index_min_max(r2, (clusidx - 1))),
17709 | mnvecs,
17710 | stan::model::rvalue(nclus, "nclus",
17711 | stan::model::index_uni(gg)),
17712 | stan::model::rvalue(Xvar, "Xvar",
17713 | stan::model::index_uni(gg)),
17714 | stan::model::rvalue(Xbetvar, "Xbetvar",
17715 | stan::model::index_uni(gg)),
17716 | stan::model::rvalue(Nx, "Nx",
17717 | stan::model::index_uni(gg)),
17718 | stan::model::rvalue(Nx_between, "Nx_between",
17719 | stan::model::index_uni(gg)), p_tilde, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; Mat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_vt<std::is_arithmetic, Mat1, Mat2>* <anonymous> = 0; stan::require_not_eigen_row_and_col_t<Mat1, Mat2>* <anonymous> = 0]'
107 | return m1 * m2;
| ~~~^~~~
stanExports_stanmarg.h:4183:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4183 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4184 | stan::math::transpose(Sig12))), "assigning variable T2p11");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:4182:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4182 | stan::math::subtract(Sig11,
4183 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4184 | stan::math::transpose(Sig12))), "assigning variable T2p11");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; Mat2 = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:4201:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4201 | stan::math::subtract(
4202 | stan::model::rvalue(YXstar, "YXstar",
4203 | stan::model::index_uni(jj),
4204 | stan::model::index_min_max(1,
4205 | stan::model::rvalue(Nobs, "Nobs",
4206 | stan::model::index_uni(mm)))),
4207 | stan::model::rvalue(Mu, "Mu",
4208 | stan::model::index_uni(grpidx),
4209 | stan::model::index_multi(
4210 | stan::model::rvalue(obsidx, "obsidx",
4211 | stan::model::index_min_max(1,
4212 | stan::model::rvalue(Nobs, "Nobs",
4213 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >; stan::require_all_eigen_vt<std::is_arithmetic, Mat1, Mat2>* <anonymous> = 0; stan::require_not_eigen_row_and_col_t<Mat1, Mat2>* <anonymous> = 0]'
107 | return m1 * m2;
| ~~~^~~~
stanExports_stanmarg.h:4200:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4200 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4201 | stan::math::subtract(
4202 | stan::model::rvalue(YXstar, "YXstar",
4203 | stan::model::index_uni(jj),
4204 | stan::model::index_min_max(1,
4205 | stan::model::rvalue(Nobs, "Nobs",
4206 | stan::model::index_uni(mm)))),
4207 | stan::model::rvalue(Mu, "Mu",
4208 | stan::model::index_uni(grpidx),
4209 | stan::model::index_multi(
4210 | stan::model::rvalue(obsidx, "obsidx",
4211 | stan::model::index_min_max(1,
4212 | stan::model::rvalue(Nobs, "Nobs",
4213 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:4193:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4193 | stan::math::add(
4194 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx),
4195 | stan::model::index_multi(
4196 | stan::model::rvalue(obsidx, "obsidx",
4197 | stan::model::index_min_max(
4198 | (stan::model::rvalue(Nobs, "Nobs",
4199 | stan::model::index_uni(mm)) + 1), p)))),
4200 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4201 | stan::math::subtract(
4202 | stan::model::rvalue(YXstar, "YXstar",
4203 | stan::model::index_uni(jj),
4204 | stan::model::index_min_max(1,
4205 | stan::model::rvalue(Nobs, "Nobs",
4206 | stan::model::index_uni(mm)))),
4207 | stan::model::rvalue(Mu, "Mu",
4208 | stan::model::index_uni(grpidx),
4209 | stan::model::index_multi(
4210 | stan::model::rvalue(obsidx, "obsidx",
4211 | stan::model::index_min_max(1,
4212 | stan::model::rvalue(Nobs, "Nobs",
4213 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:3277:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3277 | stan::math::subtract(Sigma_b,
3278 | stan::math::multiply(Sigma_yz, stan::math::transpose(Sigma_yz_zi))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Mat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:84:12: required from 'auto stan::math::multiply(Scal, const Mat&) [with Scal = int; Mat = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::require_all_not_complex_t<Scal, typename stan::value_type<T_actual, void>::type>* <anonymous> = 0]'
84 | return c * m;
| ~~^~~
stanExports_stanmarg.h:3415:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:3414:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/elt_multiply.hpp:28:25: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, -1>; Mat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
28 | return m1.cwiseProduct(m2);
| ~~~~~~~~~~~~~~~^~~~
stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3419 | q_zz = stan::math::sum(stan::math::elt_multiply(Vinv_11, Y2Yc_zz));
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:3450:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3450 | stan::math::subtract(
3451 | stan::model::rvalue(YX, "YX",
3452 | stan::model::index_uni(((r1 - 1) + i)),
3453 | stan::model::index_multi(notbidx)),
3454 | stan::model::rvalue(mean_d, "mean_d",
3455 | stan::model::index_uni(clz),
3456 | stan::model::index_multi(uord_notbidx))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:28:12: required from 'auto stan::math::multiply(const Mat&, Scal) [with Mat = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Scal = double; stan::require_stan_scalar_t<V>* <anonymous> = 0; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_not_st_var<Scal, Mat>* <anonymous> = 0; stan::require_all_not_complex_t<Scal, typename stan::value_type<T, void>::type>* <anonymous> = 0]'
28 | return c * m;
| ~~^~~
stanExports_stanmarg.h:3486:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3486 | stan::math::multiply(
3487 | stan::math::subtract(nperclus, stan::math::to_vector(clus_size_ns)),
3488 | stan::math::sum(stan::math::elt_multiply(Sigma_w_inv, S_PW))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:3501:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3501 | stan::math::add(
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
3503 | stan::math::elt_multiply(B, stan::math::to_vector(clus_size_ns))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:3500:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3500 | stan::math::add(
3501 | stan::math::add(
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
3503 | stan::math::elt_multiply(B, stan::math::to_vector(clus_size_ns))),
3504 | q_W), L_W)), "assigning variable loglik");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:3499:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3499 | stan::math::add(
3500 | stan::math::add(
3501 | stan::math::add(
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
3503 | stan::math::elt_multiply(B, stan::math::to_vector(clus_size_ns))),
3504 | q_W), L_W)), "assigning variable loglik");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:84:12: required from 'auto stan::math::multiply(Scal, const Mat&) [with Scal = double; Mat = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::require_all_not_complex_t<Scal, typename stan::value_type<T_actual, void>::type>* <anonymous> = 0]'
84 | return c * m;
| ~~^~~
stanExports_stanmarg.h:3498:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3498 | stan::math::multiply(-.5,
3499 | stan::math::add(
3500 | stan::math::add(
3501 | stan::math::add(
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
3503 | stan::math::elt_multiply(B, stan::math::to_vector(clus_size_ns))),
3504 | q_W), L_W)), "assigning variable loglik");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3507 | stan::math::add(stan::math::multiply(nperclus, (N_within + N_both)),
3508 | stan::math::multiply(stan::math::to_vector(clus_size_ns), N_between)),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:84:12: required from 'auto stan::math::multiply(Scal, const Mat&) [with Scal = double; Mat = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::require_all_not_complex_t<Scal, typename stan::value_type<T_actual, void>::type>* <anonymous> = 0]'
84 | return c * m;
| ~~^~~
stanExports_stanmarg.h:3513:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3513 | stan::math::multiply(-.5,
3514 | stan::math::multiply(P, stan::math::log((2 * stan::math::pi()))))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<double, -1, 1>; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:3512:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3512 | stan::math::add(stan::model::deep_copy(loglik),
3513 | stan::math::multiply(-.5,
3514 | stan::math::multiply(P, stan::math::log((2 * stan::math::pi()))))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:277:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits<Eigen::Ref<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> > >::match<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
44 | DerivedAlignment = int(evaluator<Derived>::Alignment),
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from 'struct stan::ref_type_if<true, const Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>&, void>'
42 | template match<T_dec>::MatchAtCompileTime
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of 'template<class T> using stan::ref_type_t = typename stan::ref_type_if<true, T>::type [with T = const Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>&]'
54 | using ref_type_t = typename ref_type_if<true, T>::type;
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of 'template<class T> stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>&]'
17 | inline ref_type_t<T&&> to_ref(T&& a) {
| ^~~~~~
stanExports_stanmarg.h:4478:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4478 | const auto& xbar = stan::math::to_ref(xbar_arg__);
stanExports_stanmarg.h:18448:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18448 | multi_normal_suff(
18449 | stan::model::rvalue(YXstar, "YXstar",
18450 | stan::model::index_uni(jj),
18451 | stan::model::index_min_max(1,
18452 | stan::model::rvalue(Nobs, "Nobs",
18453 | stan::model::index_uni(mm)))),
18454 | stan::model::rvalue(zmat, "zmat",
18455 | stan::model::index_min_max(1,
18456 | stan::model::rvalue(Nobs, "Nobs",
18457 | stan::model::index_uni(mm))),
18458 | stan::model::index_min_max(1,
18459 | stan::model::rvalue(Nobs, "Nobs",
18460 | stan::model::index_uni(mm)))),
18461 | stan::model::rvalue(Mu, "Mu",
18462 | stan::model::index_uni(grpidx),
18463 | stan::model::index_multi(
18464 | stan::model::rvalue(obsidx, "obsidx",
18465 | stan::model::index_min_max(1,
18466 | stan::model::rvalue(Nobs, "Nobs",
18467 | stan::model::index_uni(mm)))))),
18468 | stan::model::rvalue(Sigmainv, "Sigmainv",
18469 | stan::model::index_uni(mm)), 1, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >::match<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
44 | DerivedAlignment = int(evaluator<Derived>::Alignment),
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from 'struct stan::ref_type_if<true, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>&, void>'
42 | template match<T_dec>::MatchAtCompileTime
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of 'template<class T> using stan::ref_type_t = typename stan::ref_type_if<true, T>::type [with T = const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>&]'
54 | using ref_type_t = typename ref_type_if<true, T>::type;
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of 'template<class T> stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>&]'
17 | inline ref_type_t<T&&> to_ref(T&& a) {
| ^~~~~~
stanExports_stanmarg.h:4479:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4479 | const auto& S = stan::math::to_ref(S_arg__);
stanExports_stanmarg.h:18448:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18448 | multi_normal_suff(
18449 | stan::model::rvalue(YXstar, "YXstar",
18450 | stan::model::index_uni(jj),
18451 | stan::model::index_min_max(1,
18452 | stan::model::rvalue(Nobs, "Nobs",
18453 | stan::model::index_uni(mm)))),
18454 | stan::model::rvalue(zmat, "zmat",
18455 | stan::model::index_min_max(1,
18456 | stan::model::rvalue(Nobs, "Nobs",
18457 | stan::model::index_uni(mm))),
18458 | stan::model::index_min_max(1,
18459 | stan::model::rvalue(Nobs, "Nobs",
18460 | stan::model::index_uni(mm)))),
18461 | stan::model::rvalue(Mu, "Mu",
18462 | stan::model::index_uni(grpidx),
18463 | stan::model::index_multi(
18464 | stan::model::rvalue(obsidx, "obsidx",
18465 | stan::model::index_min_max(1,
18466 | stan::model::rvalue(Nobs, "Nobs",
18467 | stan::model::index_uni(mm)))))),
18468 | stan::model::rvalue(Sigmainv, "Sigmainv",
18469 | stan::model::index_uni(mm)), 1, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 - m2;
| ~~~^~~~
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
stanExports_stanmarg.h:18448:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18448 | multi_normal_suff(
18449 | stan::model::rvalue(YXstar, "YXstar",
18450 | stan::model::index_uni(jj),
18451 | stan::model::index_min_max(1,
18452 | stan::model::rvalue(Nobs, "Nobs",
18453 | stan::model::index_uni(mm)))),
18454 | stan::model::rvalue(zmat, "zmat",
18455 | stan::model::index_min_max(1,
18456 | stan::model::rvalue(Nobs, "Nobs",
18457 | stan::model::index_uni(mm))),
18458 | stan::model::index_min_max(1,
18459 | stan::model::rvalue(Nobs, "Nobs",
18460 | stan::model::index_uni(mm)))),
18461 | stan::model::rvalue(Mu, "Mu",
18462 | stan::model::index_uni(grpidx),
18463 | stan::model::index_multi(
18464 | stan::model::rvalue(obsidx, "obsidx",
18465 | stan::model::index_min_max(1,
18466 | stan::model::rvalue(Nobs, "Nobs",
18467 | stan::model::index_uni(mm)))))),
18468 | stan::model::rvalue(Sigmainv, "Sigmainv",
18469 | stan::model::index_uni(mm)), 1, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/transpose.hpp:18:21: required from 'auto stan::math::transpose(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >; stan::require_matrix_t<T>* <anonymous> = 0]'
18 | return m.transpose();
| ~~~~~~~~~~~^~
stanExports_stanmarg.h:4503:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:18448:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18448 | multi_normal_suff(
18449 | stan::model::rvalue(YXstar, "YXstar",
18450 | stan::model::index_uni(jj),
18451 | stan::model::index_min_max(1,
18452 | stan::model::rvalue(Nobs, "Nobs",
18453 | stan::model::index_uni(mm)))),
18454 | stan::model::rvalue(zmat, "zmat",
18455 | stan::model::index_min_max(1,
18456 | stan::model::rvalue(Nobs, "Nobs",
18457 | stan::model::index_uni(mm))),
18458 | stan::model::index_min_max(1,
18459 | stan::model::rvalue(Nobs, "Nobs",
18460 | stan::model::index_uni(mm)))),
18461 | stan::model::rvalue(Mu, "Mu",
18462 | stan::model::index_uni(grpidx),
18463 | stan::model::index_multi(
18464 | stan::model::rvalue(obsidx, "obsidx",
18465 | stan::model::index_min_max(1,
18466 | stan::model::rvalue(Nobs, "Nobs",
18467 | stan::model::index_uni(mm)))))),
18468 | stan::model::rvalue(Sigmainv, "Sigmainv",
18469 | stan::model::index_uni(mm)), 1, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >; stan::require_all_eigen_vt<std::is_arithmetic, Mat1, Mat2>* <anonymous> = 0; stan::require_not_eigen_row_and_col_t<Mat1, Mat2>* <anonymous> = 0]'
107 | return m1 * m2;
| ~~~^~~~
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:18448:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18448 | multi_normal_suff(
18449 | stan::model::rvalue(YXstar, "YXstar",
18450 | stan::model::index_uni(jj),
18451 | stan::model::index_min_max(1,
18452 | stan::model::rvalue(Nobs, "Nobs",
18453 | stan::model::index_uni(mm)))),
18454 | stan::model::rvalue(zmat, "zmat",
18455 | stan::model::index_min_max(1,
18456 | stan::model::rvalue(Nobs, "Nobs",
18457 | stan::model::index_uni(mm))),
18458 | stan::model::index_min_max(1,
18459 | stan::model::rvalue(Nobs, "Nobs",
18460 | stan::model::index_uni(mm)))),
18461 | stan::model::rvalue(Mu, "Mu",
18462 | stan::model::index_uni(grpidx),
18463 | stan::model::index_multi(
18464 | stan::model::rvalue(obsidx, "obsidx",
18465 | stan::model::index_min_max(1,
18466 | stan::model::rvalue(Nobs, "Nobs",
18467 | stan::model::index_uni(mm)))))),
18468 | stan::model::rvalue(Sigmainv, "Sigmainv",
18469 | stan::model::index_uni(mm)), 1, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Mat2 = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:18448:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18448 | multi_normal_suff(
18449 | stan::model::rvalue(YXstar, "YXstar",
18450 | stan::model::index_uni(jj),
18451 | stan::model::index_min_max(1,
18452 | stan::model::rvalue(Nobs, "Nobs",
18453 | stan::model::index_uni(mm)))),
18454 | stan::model::rvalue(zmat, "zmat",
18455 | stan::model::index_min_max(1,
18456 | stan::model::rvalue(Nobs, "Nobs",
18457 | stan::model::index_uni(mm))),
18458 | stan::model::index_min_max(1,
18459 | stan::model::rvalue(Nobs, "Nobs",
18460 | stan::model::index_uni(mm)))),
18461 | stan::model::rvalue(Mu, "Mu",
18462 | stan::model::index_uni(grpidx),
18463 | stan::model::index_multi(
18464 | stan::model::rvalue(obsidx, "obsidx",
18465 | stan::model::index_min_max(1,
18466 | stan::model::rvalue(Nobs, "Nobs",
18467 | stan::model::index_uni(mm)))))),
18468 | stan::model::rvalue(Sigmainv, "Sigmainv",
18469 | stan::model::index_uni(mm)), 1, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/elt_multiply.hpp:28:25: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
28 | return m1.cwiseProduct(m2);
| ~~~~~~~~~~~~~~~^~~~
stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4497 | stan::math::elt_multiply(
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:18448:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18448 | multi_normal_suff(
18449 | stan::model::rvalue(YXstar, "YXstar",
18450 | stan::model::index_uni(jj),
18451 | stan::model::index_min_max(1,
18452 | stan::model::rvalue(Nobs, "Nobs",
18453 | stan::model::index_uni(mm)))),
18454 | stan::model::rvalue(zmat, "zmat",
18455 | stan::model::index_min_max(1,
18456 | stan::model::rvalue(Nobs, "Nobs",
18457 | stan::model::index_uni(mm))),
18458 | stan::model::index_min_max(1,
18459 | stan::model::rvalue(Nobs, "Nobs",
18460 | stan::model::index_uni(mm)))),
18461 | stan::model::rvalue(Mu, "Mu",
18462 | stan::model::index_uni(grpidx),
18463 | stan::model::index_multi(
18464 | stan::model::rvalue(obsidx, "obsidx",
18465 | stan::model::index_min_max(1,
18466 | stan::model::rvalue(Nobs, "Nobs",
18467 | stan::model::index_uni(mm)))))),
18468 | stan::model::rvalue(Sigmainv, "Sigmainv",
18469 | stan::model::index_uni(mm)), 1, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Mat2 = Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; stan::require_all_eigen_vt<std::is_arithmetic, Mat1, Mat2>* <anonymous> = 0; stan::require_not_eigen_row_and_col_t<Mat1, Mat2>* <anonymous> = 0]'
107 | return m1 * m2;
| ~~~^~~~
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:18483:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18483 | multi_normal_suff(
18484 | stan::model::rvalue(YXstar, "YXstar",
18485 | stan::model::index_uni(jj),
18486 | stan::model::index_multi(
18487 | stan::model::rvalue(xdatidx, "xdatidx",
18488 | stan::model::index_min_max(1,
18489 | stan::model::rvalue(Nx, "Nx",
18490 | stan::model::index_uni(mm)))))),
18491 | stan::model::rvalue(zmat, "zmat",
18492 | stan::model::index_min_max(1,
18493 | stan::model::rvalue(Nx, "Nx",
18494 | stan::model::index_uni(mm))),
18495 | stan::model::index_min_max(1,
18496 | stan::model::rvalue(Nx, "Nx",
18497 | stan::model::index_uni(mm)))),
18498 | stan::model::rvalue(Mu, "Mu",
18499 | stan::model::index_uni(grpidx),
18500 | stan::model::index_multi(
18501 | stan::model::rvalue(xidx, "xidx",
18502 | stan::model::index_min_max(1,
18503 | stan::model::rvalue(Nx, "Nx",
18504 | stan::model::index_uni(mm)))))),
18505 | sig_inv_update(
18506 | stan::model::rvalue(Sigmainv, "Sigmainv",
18507 | stan::model::index_uni(grpidx)), xidx,
18508 | stan::model::rvalue(Nx, "Nx",
18509 | stan::model::index_uni(mm)), (p + q),
18510 | stan::model::rvalue(logdetSigma_grp,
18511 | "logdetSigma_grp", stan::model::index_uni(grpidx)),
18512 | pstream__), 1, pstream__))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Mat2 = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:18483:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18483 | multi_normal_suff(
18484 | stan::model::rvalue(YXstar, "YXstar",
18485 | stan::model::index_uni(jj),
18486 | stan::model::index_multi(
18487 | stan::model::rvalue(xdatidx, "xdatidx",
18488 | stan::model::index_min_max(1,
18489 | stan::model::rvalue(Nx, "Nx",
18490 | stan::model::index_uni(mm)))))),
18491 | stan::model::rvalue(zmat, "zmat",
18492 | stan::model::index_min_max(1,
18493 | stan::model::rvalue(Nx, "Nx",
18494 | stan::model::index_uni(mm))),
18495 | stan::model::index_min_max(1,
18496 | stan::model::rvalue(Nx, "Nx",
18497 | stan::model::index_uni(mm)))),
18498 | stan::model::rvalue(Mu, "Mu",
18499 | stan::model::index_uni(grpidx),
18500 | stan::model::index_multi(
18501 | stan::model::rvalue(xidx, "xidx",
18502 | stan::model::index_min_max(1,
18503 | stan::model::rvalue(Nx, "Nx",
18504 | stan::model::index_uni(mm)))))),
18505 | sig_inv_update(
18506 | stan::model::rvalue(Sigmainv, "Sigmainv",
18507 | stan::model::index_uni(grpidx)), xidx,
18508 | stan::model::rvalue(Nx, "Nx",
18509 | stan::model::index_uni(mm)), (p + q),
18510 | stan::model::rvalue(logdetSigma_grp,
18511 | "logdetSigma_grp", stan::model::index_uni(grpidx)),
18512 | pstream__), 1, pstream__))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/elt_multiply.hpp:28:25: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
28 | return m1.cwiseProduct(m2);
| ~~~~~~~~~~~~~~~^~~~
stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4497 | stan::math::elt_multiply(
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:18483:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18483 | multi_normal_suff(
18484 | stan::model::rvalue(YXstar, "YXstar",
18485 | stan::model::index_uni(jj),
18486 | stan::model::index_multi(
18487 | stan::model::rvalue(xdatidx, "xdatidx",
18488 | stan::model::index_min_max(1,
18489 | stan::model::rvalue(Nx, "Nx",
18490 | stan::model::index_uni(mm)))))),
18491 | stan::model::rvalue(zmat, "zmat",
18492 | stan::model::index_min_max(1,
18493 | stan::model::rvalue(Nx, "Nx",
18494 | stan::model::index_uni(mm))),
18495 | stan::model::index_min_max(1,
18496 | stan::model::rvalue(Nx, "Nx",
18497 | stan::model::index_uni(mm)))),
18498 | stan::model::rvalue(Mu, "Mu",
18499 | stan::model::index_uni(grpidx),
18500 | stan::model::index_multi(
18501 | stan::model::rvalue(xidx, "xidx",
18502 | stan::model::index_min_max(1,
18503 | stan::model::rvalue(Nx, "Nx",
18504 | stan::model::index_uni(mm)))))),
18505 | sig_inv_update(
18506 | stan::model::rvalue(Sigmainv, "Sigmainv",
18507 | stan::model::index_uni(grpidx)), xidx,
18508 | stan::model::rvalue(Nx, "Nx",
18509 | stan::model::index_uni(mm)), (p + q),
18510 | stan::model::rvalue(logdetSigma_grp,
18511 | "logdetSigma_grp", stan::model::index_uni(grpidx)),
18512 | pstream__), 1, pstream__))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite<Eigen::Matrix<double, 2, 1> >(const char*, const char*, const Eigen::Matrix<double, 2, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, 2, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from 'void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<double, 2, 1>]'
29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | y, "finite");
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:35:15: required from 'stan::return_type_t<T_x, T_sigma, T_l> stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix<double, 2, 1>; Tb = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Tz = double; stan::require_all_eigen_st<std::is_arithmetic, Ta, Tb>* <anonymous> = 0; stan::require_arithmetic_t<Tz>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = double]'
35 | check_finite("hypergeometric_pFq", "a", a_ref);
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from 'stan::return_type_t<Ta1, Ta1, Tb, Tz> stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]'
189 | return hypergeometric_pFq(a_args, b_args, z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from 'TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double, double>]'
190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from 'auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t<std::integral_constant<bool, __v> >* <anonymous> = 0]'
306 | return internal::grad_2F1_impl<true, true, true, true>(a1, a2, b1, z,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
307 | precision, max_steps);
| ~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here
37 | = grad_2F1<true>(a + b, 1.0, a + 1, z);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<double, 2, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite<Eigen::Matrix<double, 1, 1, 0, 1, 1> >(const char*, const char*, const Eigen::Matrix<double, 1, 1, 0, 1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from 'void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<double, 1, 1, 0, 1, 1>]'
29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | y, "finite");
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:36:15: required from 'stan::return_type_t<T_x, T_sigma, T_l> stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix<double, 2, 1>; Tb = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Tz = double; stan::require_all_eigen_st<std::is_arithmetic, Ta, Tb>* <anonymous> = 0; stan::require_arithmetic_t<Tz>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = double]'
36 | check_finite("hypergeometric_pFq", "b", b_ref);
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from 'stan::return_type_t<Ta1, Ta1, Tb, Tz> stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]'
189 | return hypergeometric_pFq(a_args, b_args, z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from 'TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double, double>]'
190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from 'auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t<std::integral_constant<bool, __v> >* <anonymous> = 0]'
306 | return internal::grad_2F1_impl<true, true, true, true>(a1, a2, b1, z,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
307 | precision, max_steps);
| ~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here
37 | = grad_2F1<true>(a + b, 1.0, a + 1, z);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<double, 1, 1, 0, 1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::Matrix<double, 2, 1> >(const char*, const char*, const Eigen::Matrix<double, 2, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, 2, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<double, 2, 1>]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:39:16: required from 'stan::return_type_t<T_x, T_sigma, T_l> stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix<double, 2, 1>; Tb = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Tz = double; stan::require_all_eigen_st<std::is_arithmetic, Ta, Tb>* <anonymous> = 0; stan::require_arithmetic_t<Tz>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = double]'
39 | check_not_nan("hypergeometric_pFq", "a", a_ref);
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from 'stan::return_type_t<Ta1, Ta1, Tb, Tz> stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]'
189 | return hypergeometric_pFq(a_args, b_args, z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from 'TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double, double>]'
190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from 'auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t<std::integral_constant<bool, __v> >* <anonymous> = 0]'
306 | return internal::grad_2F1_impl<true, true, true, true>(a1, a2, b1, z,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
307 | precision, max_steps);
| ~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here
37 | = grad_2F1<true>(a + b, 1.0, a + 1, z);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<double, 2, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::Matrix<double, 1, 1, 0, 1, 1> >(const char*, const char*, const Eigen::Matrix<double, 1, 1, 0, 1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<double, 1, 1, 0, 1, 1>]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:40:16: required from 'stan::return_type_t<T_x, T_sigma, T_l> stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix<double, 2, 1>; Tb = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Tz = double; stan::require_all_eigen_st<std::is_arithmetic, Ta, Tb>* <anonymous> = 0; stan::require_arithmetic_t<Tz>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = double]'
40 | check_not_nan("hypergeometric_pFq", "b", b_ref);
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from 'stan::return_type_t<Ta1, Ta1, Tb, Tz> stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]'
189 | return hypergeometric_pFq(a_args, b_args, z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from 'TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple<double, double, double, double>]'
190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from 'auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t<std::integral_constant<bool, __v> >* <anonymous> = 0]'
306 | return internal::grad_2F1_impl<true, true, true, true>(a1, a2, b1, z,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
307 | precision, max_steps);
| ~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here
37 | = grad_2F1<true>(a + b, 1.0, a + 1, z);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<double, 1, 1, 0, 1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, member_sum<double, double>, 1>; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
466 | return maxCoeff<PropagateFast>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here
106 | return x.cwiseAbs().rowwise().sum().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15: required from 'PacketType Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; int Direction = 1; Eigen::Index = long long int]'
203 | PanelType panel(m_arg,
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >; Scalar = double]'
251 | PacketScalar packet_res0 = eval.template packet<alignment,PacketScalar>(alignedStart);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
466 | return maxCoeff<PropagateFast>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here
106 | return x.cwiseAbs().rowwise().sum().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true> >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:217:20: required from 'PacketType Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; int Direction = 1; Eigen::Index = long long int]'
217 | PanelEvaluator panel_eval(panel);
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >; Scalar = double]'
251 | PacketScalar packet_res0 = eval.template packet<alignment,PacketScalar>(alignedStart);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
466 | return maxCoeff<PropagateFast>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here
106 | return x.cwiseAbs().rowwise().sum().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: required from 'const Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::Scalar Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; int Direction = 1; Scalar = double; Eigen::Index = long long int]'
183 | return m_functor(m_arg.template subVector<DirectionType(Direction)>(index));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >; Scalar = double]'
268 | res = func(res,eval.coeff(index));
| ~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
466 | return maxCoeff<PropagateFast>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here
106 | return x.cwiseAbs().rowwise().sum().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_rhs<Scalar, Index, DataMapper, nr, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::const_blas_data_mapper<double, long long int, 0>; int nr = 4; bool Conjugate = false; bool PanelMode = false]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:100:15: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
100 | pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, size);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2459 | PacketBlock<Packet,(PacketSize%4)==0?4:PacketSize> kernel;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, Packet, 1, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::const_blas_data_mapper<double, long long int, 1>; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:106:17: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
106 | pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2256:82: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2256 | typedef typename unpacket_traits<typename unpacket_traits<Packet>::half>::half QuarterPacket;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2258:56: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2258 | HalfPacketSize = unpacket_traits<HalfPacket>::size,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2259 | QuarterPacketSize = unpacket_traits<QuarterPacket>::size,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2298 | PacketBlock<HalfPacket> kernel_half;
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2304 | PacketBlock<QuarterPacket> kernel_quarter;
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gebp_kernel<LhsScalar, RhsScalar, Index, DataMapper, mr, nr, ConjugateLhs, ConjugateRhs>::operator()(const DataMapper&, const LhsScalar*, const RhsScalar*, Index, Index, Index, ResScalar, Index, Index, Index, Index) [with LhsScalar = double; RhsScalar = double; Index = long long int; DataMapper = Eigen::internal::blas_data_mapper<double, long long int, 0, 0, 1>; int mr = 4; int nr = 4; bool ConjugateLhs = false; bool ConjugateRhs = false; ResScalar = double]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:113:15: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
113 | gebp(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc,
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
114 | (std::min)(size,i2), alpha, -1, -1, 0, 0);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1920:103: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
1920 | const int SResPacketHalfSize = unpacket_traits<typename unpacket_traits<SResPacket>::half>::size;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
1921 | const int SResPacketQuarterSize = unpacket_traits<typename unpacket_traits<typename unpacket_traits<SResPacket>::half>::half>::size;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1977:135: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
1977 | typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SResPacket>::half,SResPacket>::type SResPacketHalf;
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1978:135: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
1978 | typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SLhsPacket>::half,SLhsPacket>::type SLhsPacketHalf;
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1979:135: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
1979 | typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SRhsPacket>::half,SRhsPacket>::type SRhsPacketHalf;
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1980:135: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
1980 | typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SAccPacket>::half,SAccPacket>::type SAccPacketHalf;
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, 16>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<double, 4, 4> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 4> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, 4, 4>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:155:52: required from 'void Eigen::internal::tribb_kernel<LhsScalar, RhsScalar, Index, mr, nr, ConjLhs, ConjRhs, ResInnerStride, UpLo>::operator()(ResScalar*, Index, Index, const LhsScalar*, const RhsScalar*, Index, Index, const ResScalar&) [with LhsScalar = double; RhsScalar = double; Index = long long int; int mr = 4; int nr = 4; bool ConjLhs = false; bool ConjRhs = false; int ResInnerStride = 1; int UpLo = 2; ResScalar = double]'
155 | Matrix<ResScalar,BlockSize,BlockSize,ColMajor> buffer((internal::constructor_without_unaligned_array_assert()));
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha);
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 4, 4> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 4, 4> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 4> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha);
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here
28 | double variance = diff.squaredNorm() / size_m1;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:46: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
370 | * (conj(h) * matA.col(i).tail(remainingSize)));
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
370 | * (conj(h) * matA.col(i).tail(remainingSize)));
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:26: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:43: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:352:35: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
352 | Block<MatrixType,Dynamic,1> A21(mat,k+1,k,rs,1);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:80: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:67: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0, 6>'
126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:35: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value();
| ~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:32: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
361 | A21.noalias() -= A20 * temp.head(k);
| ~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:56: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:32: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
387 | ret = ret && (A21.array()==Scalar(0)).all();
| ~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:887:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:120:49: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_L(const T&, size_t, stan::value_type_t<T>&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
120 | acc += (K - k - 1) * log1m(square(CPCs_ref(pos)));
| ~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:55: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t<T>&) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:37:52: required from 'stan::math::matrix_d stan::math::multiply_lower_tri_self_transpose(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_matrix_dynamic_t<EigMat>* <anonymous> = 0; stan::require_not_st_autodiff<EigMat>* <anonymous> = 0; matrix_d = Eigen::Matrix<double, -1, -1>]'
37 | LLt(n, m) = LLt(m, n) = Lt.col(m).head(k).dot(Lt.col(n).head(k));
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t<T>&) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:32:27: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
32 | sds = Sigma_ref.diagonal().array();
| ~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:32:35: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
32 | sds = Sigma_ref.diagonal().array();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Array<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:36:17: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
36 | sds = sds.sqrt();
| ~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:39:29: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
39 | D.diagonal() = sds.inverse();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:40:16: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
40 | sds = sds.log(); // now unbounded
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:42:65: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
42 | Eigen::Matrix<T_scalar, Eigen::Dynamic, Eigen::Dynamic> R = D * Sigma_ref * D;
| ~~^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix<double, -1, -1>, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix<double, -1, -1>, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix<double, -1, -1>, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix<double, -1, -1>, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix<double, -1, -1>, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::DiagonalMatrix<double, -1, -1>, Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix<double, -1, -1>, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:42:77: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
42 | Eigen::Matrix<T_scalar, Eigen::Dynamic, Eigen::Dynamic> R = D * Sigma_ref * D;
| ~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1> >(Eigen::Matrix<double, -1, 1>&&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1> >(Eigen::Matrix<double, -1, 1>&&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1> >(Eigen::Matrix<double, -1, 1>&&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1> >(Eigen::Matrix<double, -1, 1>&&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:158:0: required from 'stan::model::rvalue<Eigen::Matrix<double, -1, 1> >(Eigen::Matrix<double, -1, 1>&&, const char*, const index_multi&)::<lambda(auto:767&)> [with auto:767 = Eigen::Matrix<double, -1, 1>]'
158 | return plain_type_t<EigVec>::NullaryExpr(
159 | idx.ns_.size(), [name, &idx, &v_ref](Eigen::Index i) {
160 | math::check_range("vector[multi] indexing", name, v_ref.size(),
161 | idx.ns_[i]);
162 | return v_ref.coeff(idx.ns_[i] - 1);
163 | });
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue<Eigen::Matrix<double, -1, 1> >(Eigen::Matrix<double, -1, 1>&&, const char*, const index_multi&)::<lambda(auto:767&)>; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:156:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14456:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14456 | stan::model::rvalue(YXstar, "YXstar",
14457 | stan::model::index_min_max(r1, r2),
14458 | stan::model::index_multi(
14459 | stan::model::rvalue(xdatidx, "xdatidx",
14460 | stan::model::index_min_max(1,
14461 | stan::model::rvalue(Nx, "Nx",
14462 | stan::model::index_uni(mm)))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:77:13: required from 'auto stan::math::add(Scal, const Mat&) [with Scal = int; Mat = Eigen::Matrix<double, -1, 1>; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
77 | return (c + m.array()).matrix();
| ~~~^~~~~~~~~~~~
stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:77:32: required from 'auto stan::math::add(Scal, const Mat&) [with Scal = int; Mat = Eigen::Matrix<double, -1, 1>; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
77 | return (c + m.array()).matrix();
| ~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:84:12: required from 'auto stan::math::multiply(Scal, const Mat&) [with Scal = double; Mat = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::require_all_not_complex_t<Scal, typename stan::value_type<T_actual, void>::type>* <anonymous> = 0]'
84 | return c * m;
| ~~^~~
stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_linesearch.hpp:247:0: required from 'int stan::optimization::WolfeLineSearch(FunctorType&, Scalar&, XType&, Scalar&, XType&, const XType&, const XType&, const Scalar&, const XType&, const Scalar&, const Scalar&, const Scalar&, const Scalar&, const Scalar&) [with FunctorType = ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; Scalar = double; XType = Eigen::Matrix<double, -1, 1>]'
247 | x1.noalias() = x0 + alpha1 * p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:209:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
209 | = WolfeLineSearch(_func, _alpha, _xk_1, _fk_1, _gk_1, _pk, _xk, _fk,
210 | _gk, _ls_opts.c1, _ls_opts.c2, _ls_opts.minAlpha,
211 | _ls_opts.maxLSIts, _ls_opts.maxLSRestarts);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:55:0: required from 'void stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::search_direction(VectorT&, const VectorT&) const [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
55 | pk.noalias() = -(_Hk * gk);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:254:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
254 | _qn.search_direction(_pk, _gk);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Inverse.h:68:7: required from 'class Eigen::InverseImpl<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> >, Eigen::SolverStorage>'
68 | class InverseImpl
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Inverse.h:43:7: required from 'class Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > >'
43 | class Inverse : public InverseImpl<XprType,typename internal::traits<XprType>::StorageKind>
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_determinant.hpp:23:0: required from 'stan::math::var stan::math::log_determinant(const T&) [with T = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_rev_matrix_t<T>* <anonymous> = 0; var = var_value<double>]'
23 | auto arena_m_inv_transpose = to_arena(m_hh.inverse().transpose());
stanExports_stanmarg.h:14144:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14144 | stan::math::log_determinant(
14145 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_determinant.hpp:23:0: required from 'stan::math::var stan::math::log_determinant(const T&) [with T = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_rev_matrix_t<T>* <anonymous> = 0; var = var_value<double>]'
23 | auto arena_m_inv_transpose = to_arena(m_hh.inverse().transpose());
stanExports_stanmarg.h:14144:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14144 | stan::math::log_determinant(
14145 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_determinant.hpp:27:0: required from 'stan::math::var stan::math::log_determinant(const T&) [with T = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_rev_matrix_t<T>* <anonymous> = 0; var = var_value<double>]'
27 | arena_m.adj() += log_det.adj() * arena_m_inv_transpose;
stanExports_stanmarg.h:14144:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14144 | stan::math::log_determinant(
14145 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >&)::<lambda(auto:11&)> [with auto:11 = const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1>, 0>; Types = {Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> >, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; T2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
55 | using return_t
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> >, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; T2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
65 | using return_t
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:121:0: required from 'auto stan::math::subtract(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
121 | using ret_type = return_var_matrix_t<op_ret_type, VarMat1, VarMat2>;
stanExports_stanmarg.h:4436:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:124:0: required from 'auto stan::math::subtract(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix<var_value<double>, -1, -1>; VarMat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]'
124 | arena_t<ret_type> ret((arena_a.val() - arena_b.val()));
stanExports_stanmarg.h:4436:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0>; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1> >}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, -1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
55 | using return_t
stanExports_stanmarg.h:3278:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3278 | stan::math::multiply(Sigma_yz, stan::math::transpose(Sigma_yz_zi))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::Matrix<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
180 | (as_array_or_scalar(a) - b.val().array()).matrix())>;
stanExports_stanmarg.h:3309:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > > >'
29 | = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::value
| ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template<class T> struct stan::plain_type<T, typename std::enable_if<stan::math::conjunction<stan::is_var<T, void>, stan::is_eigen<typename stan::value_type<T, void>::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >]'
22 | using plain_type_t = typename plain_type<T>::type;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template<class T> using stan::plain_type_t = typename stan::plain_type<T>::type [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >]'
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:179:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::Matrix<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
179 | using op_ret_type = plain_type_t<decltype(
stanExports_stanmarg.h:3309:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:183:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::Matrix<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
183 | arena_t<ret_type> ret(as_array_or_scalar(a) - arena_b.val().array());
stanExports_stanmarg.h:3309:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/tcrossprod.hpp:28:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/tcrossprod.hpp:28:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/tcrossprod.hpp:33:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/tcrossprod.hpp:33:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/tcrossprod.hpp:33:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix());
stanExports_stanmarg.h:3351:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3351 | stan::math::add(stan::model::deep_copy(Y2Yc),
3352 | stan::model::rvalue(cov_d, "cov_d", stan::model::index_uni(clz))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >'
29 | = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::value
| ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
148 | using ret_type = return_var_matrix_t<op_ret_type, VarMat>;
stanExports_stanmarg.h:3351:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3351 | stan::math::add(stan::model::deep_copy(Y2Yc),
3352 | stan::model::rvalue(cov_d, "cov_d", stan::model::index_uni(clz))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
150 | arena_t<ret_type> ret(arena_a.val().array() + as_array_or_scalar(b));
stanExports_stanmarg.h:3351:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3351 | stan::math::add(stan::model::deep_copy(Y2Yc),
3352 | stan::model::rvalue(cov_d, "cov_d", stan::model::index_uni(clz))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:145:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = int; T2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
145 | arena_t<return_t> res = arena_A.val() * arena_B.val().array();
stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:163:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = int; T2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
163 | arena_B.adj().array() += arena_A * res.adj().array();
stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, -1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:170:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = int; T2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
170 | arena_t<return_t> res = arena_A.val() * arena_B.array();
stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:172:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = int; T2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
172 | arena_A.adj() += (res.adj().array() * arena_B.array()).sum();
stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:31:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, -1>; Mat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
31 | using ret_type = return_var_matrix_t<inner_ret_type, Mat1, Mat2>;
stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3419 | q_zz = stan::math::sum(stan::math::elt_multiply(Vinv_11, Y2Yc_zz));
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:35:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, -1>; Mat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
35 | arena_t<ret_type> ret(arena_m1.val().cwiseProduct(arena_m2.val()));
stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3419 | q_zz = stan::math::sum(stan::math::elt_multiply(Vinv_11, Y2Yc_zz));
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:49:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, -1>; Mat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
49 | arena_t<ret_type> ret(arena_m1.val().cwiseProduct(arena_m2));
stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3419 | q_zz = stan::math::sum(stan::math::elt_multiply(Vinv_11, Y2Yc_zz));
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:51:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, -1>; Mat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
51 | arena_m1.adj().array() += arena_m2.array() * ret.adj().array();
stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3419 | q_zz = stan::math::sum(stan::math::elt_multiply(Vinv_11, Y2Yc_zz));
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:57:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, -1>; Mat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
57 | arena_t<ret_type> ret(arena_m1.cwiseProduct(arena_m2.val()));
stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3419 | q_zz = stan::math::sum(stan::math::elt_multiply(Vinv_11, Y2Yc_zz));
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:154:0: required from 'auto stan::math::subtract(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
154 | (a.val().array() - as_array_or_scalar(b)).matrix())>;
stanExports_stanmarg.h:3487:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3487 | stan::math::subtract(nperclus, stan::math::to_vector(clus_size_ns)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >'
29 | = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::value
| ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template<class T> struct stan::plain_type<T, typename std::enable_if<stan::math::conjunction<stan::is_var<T, void>, stan::is_eigen<typename stan::value_type<T, void>::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >]'
22 | using plain_type_t = typename plain_type<T>::type;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template<class T> using stan::plain_type_t = typename stan::plain_type<T>::type [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >]'
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:153:0: required from 'auto stan::math::subtract(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
153 | using op_ret_type = plain_type_t<decltype(
stanExports_stanmarg.h:3487:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3487 | stan::math::subtract(nperclus, stan::math::to_vector(clus_size_ns)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:157:0: required from 'auto stan::math::subtract(const VarMat&, const Arith&) [with Arith = Eigen::Matrix<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
157 | arena_t<ret_type> ret(arena_a.val().array() - as_array_or_scalar(b));
stanExports_stanmarg.h:3487:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3487 | stan::math::subtract(nperclus, stan::math::to_vector(clus_size_ns)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::Matrix<double, -1, 1, 0, -1, 1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:31:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, 1>; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
31 | using ret_type = return_var_matrix_t<inner_ret_type, Mat1, Mat2>;
stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:35:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, 1>; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
35 | arena_t<ret_type> ret(arena_m1.val().cwiseProduct(arena_m2.val()));
stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:49:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, 1>; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
49 | arena_t<ret_type> ret(arena_m1.val().cwiseProduct(arena_m2));
stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:51:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, 1>; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
51 | arena_m1.adj().array() += arena_m2.array() * ret.adj().array();
stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:57:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix<var_value<double>, -1, 1>; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
57 | arena_t<ret_type> ret(arena_m1.cwiseProduct(arena_m2.val()));
stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >&>(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:13&)> [with auto:13 = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >&>(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:13&)>; Args = {const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1, 0, -1, 1> >, const Eigen::Matrix<double, -1, 1, 0, -1, 1> >&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3507 | stan::math::add(stan::math::multiply(nperclus, (N_within + N_both)),
3508 | stan::math::multiply(stan::math::to_vector(clus_size_ns), N_between)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix());
stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3507 | stan::math::add(stan::math::multiply(nperclus, (N_within + N_both)),
3508 | stan::math::multiply(stan::math::to_vector(clus_size_ns), N_between)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >'
29 | = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::value
| ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
148 | using ret_type = return_var_matrix_t<op_ret_type, VarMat>;
stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3507 | stan::math::add(stan::math::multiply(nperclus, (N_within + N_both)),
3508 | stan::math::multiply(stan::math::to_vector(clus_size_ns), N_between)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
150 | arena_t<ret_type> ret(arena_a.val().array() + as_array_or_scalar(b));
stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3507 | stan::math::add(stan::math::multiply(nperclus, (N_within + N_both)),
3508 | stan::math::multiply(stan::math::to_vector(clus_size_ns), N_between)),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_ldlt.hpp:32:0: required from 'auto stan::math::mdivide_left_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]'
32 | check_multiplicable("mdivide_left_ldlt", "A", A.matrix().val(), "B", B);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_ldlt.hpp:41:0: required from 'auto stan::math::mdivide_left_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]'
41 | arena_t<ret_type> res = A.ldlt().solve(arena_B.val());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_ldlt.hpp:45:0: required from 'auto stan::math::mdivide_left_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]'
45 | promote_scalar_t<double, T2> adjB = ldlt_ptr->solve(res.adj());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits<Eigen::Ref<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> > >::match<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
44 | DerivedAlignment = int(evaluator<Derived>::Alignment),
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from 'struct stan::ref_type_if<true, const Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>&, void>'
42 | template match<T_dec>::MatchAtCompileTime
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of 'template<class T> using stan::ref_type_t = typename stan::ref_type_if<true, T>::type [with T = const Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>&]'
54 | using ref_type_t = typename ref_type_if<true, T>::type;
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of 'template<class T> stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>&]'
17 | inline ref_type_t<T&&> to_ref(T&& a) {
| ^~~~~~
stanExports_stanmarg.h:4478:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4478 | const auto& xbar = stan::math::to_ref(xbar_arg__);
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >::match<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
44 | DerivedAlignment = int(evaluator<Derived>::Alignment),
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from 'struct stan::ref_type_if<true, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>&, void>'
42 | template match<T_dec>::MatchAtCompileTime
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of 'template<class T> using stan::ref_type_t = typename stan::ref_type_if<true, T>::type [with T = const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>&]'
54 | using ref_type_t = typename ref_type_if<true, T>::type;
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of 'template<class T> stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>&]'
17 | inline ref_type_t<T&&> to_ref(T&& a) {
| ^~~~~~
stanExports_stanmarg.h:4479:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4479 | const auto& S = stan::math::to_ref(S_arg__);
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar<const Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>&>(const Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>&)::<lambda(auto:13&)> [with auto:13 = const Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:180:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
180 | (as_array_or_scalar(a) - b.val().array()).matrix())>;
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > > >'
29 | = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::value
| ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template<class T> struct stan::plain_type<T, typename std::enable_if<stan::math::conjunction<stan::is_var<T, void>, stan::is_eigen<typename stan::value_type<T, void>::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >]'
22 | using plain_type_t = typename plain_type<T>::type;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template<class T> using stan::plain_type_t = typename stan::plain_type<T>::type [with T = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >]'
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:179:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
179 | using op_ret_type = plain_type_t<decltype(
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_subtraction.hpp:183:0: required from 'auto stan::math::subtract(const Arith&, const VarMat&) [with Arith = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
183 | arena_t<ret_type> ret(as_array_or_scalar(a) - arena_b.val().array());
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, 1>; T2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
36 | using return_t
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&>(const Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >&)::<lambda(auto:11&)> [with auto:11 = const Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, 1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, 1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, 1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, 1, -1>, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, 1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, 1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, 1, -1>, 0>; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, 1>; T2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
55 | using return_t
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, 1>; T2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
57 | arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, 1>, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, 1>, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::Transpose<const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, 1>; T2 = Eigen::Transpose<const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
65 | using return_t
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>&)::<lambda(auto:13&)> [with auto:13 = const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >'
140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > > >'
29 | = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::value
| ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from 'auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
148 | using ret_type = return_var_matrix_t<op_ret_type, VarMat>;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from 'auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; VarMat = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]'
169 | return add(b, a);
stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)> [with auto:11 = const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4497 | stan::math::elt_multiply(
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; Types = {Eigen::Block<const Eigen::Block<Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:31:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block<const Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>, -1, -1, false>; Mat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
31 | using ret_type = return_var_matrix_t<inner_ret_type, Mat1, Mat2>;
stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4497 | stan::math::elt_multiply(
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)> [with auto:11 = const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Matrix<double, -1, -1>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4497 | stan::math::elt_multiply(
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14525:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14525 | multi_normal_suff(
14526 | stan::model::rvalue(YXbarstar, "YXbarstar",
14527 | stan::model::index_uni(mm),
14528 | stan::model::index_multi(
14529 | stan::model::rvalue(xdatidx, "xdatidx",
14530 | stan::model::index_min_max(1,
14531 | stan::model::rvalue(Nx, "Nx",
14532 | stan::model::index_uni(mm)))))),
14533 | stan::model::rvalue(Sstar, "Sstar",
14534 | stan::model::index_uni(mm),
14535 | stan::model::index_multi(
14536 | stan::model::rvalue(xdatidx, "xdatidx",
14537 | stan::model::index_min_max(1,
14538 | stan::model::rvalue(Nx, "Nx",
14539 | stan::model::index_uni(mm))))),
14540 | stan::model::index_multi(
14541 | stan::model::rvalue(xdatidx, "xdatidx",
14542 | stan::model::index_min_max(1,
14543 | stan::model::rvalue(Nx, "Nx",
14544 | stan::model::index_uni(mm)))))),
14545 | stan::model::rvalue(Mu, "Mu",
14546 | stan::model::index_uni(grpidx),
14547 | stan::model::index_multi(
14548 | stan::model::rvalue(xidx, "xidx",
14549 | stan::model::index_min_max(1,
14550 | stan::model::rvalue(Nx, "Nx",
14551 | stan::model::index_uni(mm)))))),
14552 | sig_inv_update(
14553 | stan::model::rvalue(Sigmainv, "Sigmainv",
14554 | stan::model::index_uni(mm)), xidx,
14555 | stan::model::rvalue(Nx, "Nx",
14556 | stan::model::index_uni(mm)), (p + q),
14557 | stan::model::rvalue(logdetSigma_grp,
14558 | "logdetSigma_grp", stan::model::index_uni(grpidx)),
14559 | pstream__), ((r2 - r1) + 1), pstream__)));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&>(const Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Block<const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; Types = {Eigen::Block<const Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>, -1, -1, false>, Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>}]'
23 | is_any_var_matrix<ReturnType, Types...>::value,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:31:0: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block<const Eigen::Matrix<var_value<double>, -1, -1>, -1, -1, false>; Mat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]'
31 | using ret_type = return_var_matrix_t<inner_ret_type, Mat1, Mat2>;
stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Matrix<double, -1, -1>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4497 | stan::math::elt_multiply(
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14525:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14525 | multi_normal_suff(
14526 | stan::model::rvalue(YXbarstar, "YXbarstar",
14527 | stan::model::index_uni(mm),
14528 | stan::model::index_multi(
14529 | stan::model::rvalue(xdatidx, "xdatidx",
14530 | stan::model::index_min_max(1,
14531 | stan::model::rvalue(Nx, "Nx",
14532 | stan::model::index_uni(mm)))))),
14533 | stan::model::rvalue(Sstar, "Sstar",
14534 | stan::model::index_uni(mm),
14535 | stan::model::index_multi(
14536 | stan::model::rvalue(xdatidx, "xdatidx",
14537 | stan::model::index_min_max(1,
14538 | stan::model::rvalue(Nx, "Nx",
14539 | stan::model::index_uni(mm))))),
14540 | stan::model::index_multi(
14541 | stan::model::rvalue(xdatidx, "xdatidx",
14542 | stan::model::index_min_max(1,
14543 | stan::model::rvalue(Nx, "Nx",
14544 | stan::model::index_uni(mm)))))),
14545 | stan::model::rvalue(Mu, "Mu",
14546 | stan::model::index_uni(grpidx),
14547 | stan::model::index_multi(
14548 | stan::model::rvalue(xidx, "xidx",
14549 | stan::model::index_min_max(1,
14550 | stan::model::rvalue(Nx, "Nx",
14551 | stan::model::index_uni(mm)))))),
14552 | sig_inv_update(
14553 | stan::model::rvalue(Sigmainv, "Sigmainv",
14554 | stan::model::index_uni(mm)), xidx,
14555 | stan::model::rvalue(Nx, "Nx",
14556 | stan::model::index_uni(mm)), (p + q),
14557 | stan::model::rvalue(logdetSigma_grp,
14558 | "logdetSigma_grp", stan::model::index_uni(grpidx)),
14559 | pstream__), ((r2 - r1) + 1), pstream__)));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:11&)> [with auto:11 = Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:58:64: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
58 | decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:13&)> [with auto:13 = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:60:68: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
60 | decltype(auto) sigma_val = to_ref(as_value_column_array_or_scalar(sigma_ref));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from 'stan::math::inv<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:220&)> [with auto:220 = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >]'
55 | x, [](const auto& v) { return v.array().inverse(); });
| ~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:76:68: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
76 | = to_ref_if<!is_constant_all<T_y, T_scale, T_loc>::value>(inv(sigma_val));
| ~~~^~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:40: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma);
| ~~~~~~~^~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:50: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:79:62: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
79 | = to_ref_if<!is_constant_all<T_scale>::value>(y_scaled * y_scaled);
| ~~~~~~~~~^~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:169&)> [with auto:169 = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:20: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
87 | logp -= sum(log(sigma_val)) * N / math::size(sigma);
| ~~~^~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:35: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
96 | partials<0>(ops_partials) = -scaled_diff;
| ^~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:45: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
| ~~~~~~~~~~^~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:59: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:94:23: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
94 | logp = -sum(lgamma(alpha_val)) * N / math::size(alpha);
| ~~~~~~^~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:27: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
100 | logp += sum(alpha_val * log_beta) * N / max_size(alpha, beta);
| ~~~~~~~~~~^~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:44: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val);
| ~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:61: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val);
| ~~~~~~~^~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:52: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:28: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
106 | logp += sum((alpha_val - 1.0) * log_y) * N / max_size(alpha, y);
| ~~~~~~~~~~~^~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:35: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
106 | logp += sum((alpha_val - 1.0) * log_y) * N / max_size(alpha, y);
| ~~~~~~~~~~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y);
| ~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:44: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
| ~~~~~~~~~~~^~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
| ~~~~~~~~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:43: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val;
| ~~~~~~~~~~^~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val;
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:3&&)>, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:3&&)>, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:3&&)>, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:3&&)>, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1m_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:3&&)>, const Eigen::Array<double, -1, 1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1m_fun; T = Eigen::Array<double, -1, 1>]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:79:37: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
79 | const auto& log1m_y = to_ref(log1m(y_val));
| ~~~~~^~~~~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:99:61: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
99 | = (alpha_val - 1) / y_val + (beta_val - 1) / (y_val - 1);
| ~~~~~~~^~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:99:52: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
99 | = (alpha_val - 1) / y_val + (beta_val - 1) / (y_val - 1);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:99:35: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
99 | = (alpha_val - 1) / y_val + (beta_val - 1) / (y_val - 1);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:105:23: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
105 | alpha_val + beta_val);
| ~~~~~~~~~~^~~~~~~~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:106:23: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
106 | logp += sum(lgamma(alpha_beta)) * N / max_size(alpha, beta);
| ~~~~~~^~~~~~~~~~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >]'
62 | return x.unaryExpr([](auto&& x) {
| ~~~~~~~~~~~^~~~~~~~~~~~~~~
63 | return apply_scalar_unary<F, std::decay_t<decltype(x)>>::apply(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
64 | });
| ~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:110:64: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
110 | && !is_constant_all<T_scale_fail>::value > (digamma(alpha_beta));
| ~~~~~~~^~~~~~~~~~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:113:21: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
113 | = log_y + digamma_alpha_beta - digamma(alpha_val);
| ~~~~~~^~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::<lambda(auto:3&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:3&&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:113:42: required from 'stan::return_type_t<T, L, U> stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_scale_succ = std::vector<double>; T_scale_fail = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
113 | = log_y + digamma_alpha_beta - digamma(alpha_val);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:887:41: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_symmetric.hpp:41:29: required from 'void stan::math::check_symmetric(const char*, const char*, const EigMat&) [with EigMat = Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >; stan::require_matrix_t<T>* <anonymous> = 0]'
41 | const auto& y_ref = to_ref(y);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:32:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; typename stan::value_type<T>::type = double]'
32 | check_symmetric("inverse_spd", "m", m_ref);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:16304:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16304 | stan::math::inverse_spd(
16305 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:463:34: required from 'typename MatrixType::RealScalar Eigen::ColPivHouseholderQR<MatrixType>::logAbsDeterminant() const [with _MatrixType = Eigen::Matrix<double, -1, -1>; typename MatrixType::RealScalar = double]'
463 | return m_qr.diagonal().cwiseAbs().array().log().sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:51: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:463:42: required from 'typename MatrixType::RealScalar Eigen::ColPivHouseholderQR<MatrixType>::logAbsDeterminant() const [with _MatrixType = Eigen::Matrix<double, -1, -1>; typename MatrixType::RealScalar = double]'
463 | return m_qr.diagonal().cwiseAbs().array().log().sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:51: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:463:48: required from 'typename MatrixType::RealScalar Eigen::ColPivHouseholderQR<MatrixType>::logAbsDeterminant() const [with _MatrixType = Eigen::Matrix<double, -1, -1>; typename MatrixType::RealScalar = double]'
463 | return m_qr.diagonal().cwiseAbs().array().log().sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:51: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LLT<Eigen::Matrix<double, -1, -1>, 1>, Eigen::Matrix<double, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LLT<Eigen::Matrix<double, -1, -1>, 1>, Eigen::Matrix<double, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LLT<Eigen::Matrix<double, -1, -1>, 1>, Eigen::Matrix<double, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LLT<Eigen::Matrix<double, -1, -1>, 1>, Eigen::Matrix<double, -1, -1>, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LLT<Eigen::Matrix<double, -1, -1>, 1>, Eigen::Matrix<double, -1, -1> >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_left_spd.hpp:46:19: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_left_spd(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_var<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
46 | return llt.solve(
| ~~~~~~~~~^
47 | Eigen::Matrix<return_type_t<EigMat1, EigMat2>, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
48 | EigMat2::ColsAtCompileTime>(b));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:4445:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4498:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
stanExports_stanmarg.h:4825:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix<double, -1, 1>; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = Eigen::Matrix<double, -1, -1>; T4__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__>, stan::is_eigen_matrix_dynamic<T4__>, stan::is_vt_not_complex<T9__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; typename stan::base_type<T9__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4825 | multi_normal_suff(
4826 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4827 | stan::model::index_multi(
4828 | stan::model::rvalue(Xvar, "Xvar",
4829 | stan::model::index_min_max(1, Nx)))),
4830 | stan::model::rvalue(cov_w, "cov_w",
4831 | stan::model::index_min_max(1, Nx),
4832 | stan::model::index_min_max(1, Nx)),
4833 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4834 | stan::model::index_multi(
4835 | stan::model::rvalue(Xvar, "Xvar",
4836 | stan::model::index_min_max(1, Nx)))),
4837 | stan::model::rvalue(cov_w_inv, "cov_w_inv",
4838 | stan::model::index_min_max(1, (Nx + 1)),
4839 | stan::model::index_min_max(1, (Nx + 1))),
4840 | stan::model::rvalue(cluster_size, "cluster_size",
4841 | stan::model::index_uni(cc)), pstream__)),
stanExports_stanmarg.h:17723:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17723 | calc_log_lik_x(
17724 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17725 | stan::model::index_min_max(r2, (clusidx - 1))),
17726 | stan::model::rvalue(mnvecs, "mnvecs",
17727 | stan::model::index_uni(2)),
17728 | stan::model::rvalue(covmats, "covmats",
17729 | stan::model::index_uni(1)),
17730 | stan::model::rvalue(covmats, "covmats",
17731 | stan::model::index_uni(2)),
17732 | stan::model::rvalue(covmats, "covmats",
17733 | stan::model::index_uni(3)),
17734 | stan::model::rvalue(nclus, "nclus",
17735 | stan::model::index_uni(gg)),
17736 | stan::model::rvalue(cluster_size, "cluster_size",
17737 | stan::model::index_min_max(r2, (clusidx - 1))),
17738 | stan::model::rvalue(Xvar, "Xvar",
17739 | stan::model::index_uni(gg)),
17740 | stan::model::rvalue(Xbetvar, "Xbetvar",
17741 | stan::model::index_uni(gg)),
17742 | stan::model::rvalue(Nx, "Nx",
17743 | stan::model::index_uni(gg)),
17744 | stan::model::rvalue(Nx_between, "Nx_between",
17745 | stan::model::index_uni(gg)), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; Mat2 = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
45 | return m1 + m2;
| ~~~^~~~
stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:4825:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix<double, -1, 1>; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = Eigen::Matrix<double, -1, -1>; T4__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__>, stan::is_eigen_matrix_dynamic<T4__>, stan::is_vt_not_complex<T9__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; typename stan::base_type<T9__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4825 | multi_normal_suff(
4826 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4827 | stan::model::index_multi(
4828 | stan::model::rvalue(Xvar, "Xvar",
4829 | stan::model::index_min_max(1, Nx)))),
4830 | stan::model::rvalue(cov_w, "cov_w",
4831 | stan::model::index_min_max(1, Nx),
4832 | stan::model::index_min_max(1, Nx)),
4833 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4834 | stan::model::index_multi(
4835 | stan::model::rvalue(Xvar, "Xvar",
4836 | stan::model::index_min_max(1, Nx)))),
4837 | stan::model::rvalue(cov_w_inv, "cov_w_inv",
4838 | stan::model::index_min_max(1, (Nx + 1)),
4839 | stan::model::index_min_max(1, (Nx + 1))),
4840 | stan::model::rvalue(cluster_size, "cluster_size",
4841 | stan::model::index_uni(cc)), pstream__)),
stanExports_stanmarg.h:17723:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17723 | calc_log_lik_x(
17724 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17725 | stan::model::index_min_max(r2, (clusidx - 1))),
17726 | stan::model::rvalue(mnvecs, "mnvecs",
17727 | stan::model::index_uni(2)),
17728 | stan::model::rvalue(covmats, "covmats",
17729 | stan::model::index_uni(1)),
17730 | stan::model::rvalue(covmats, "covmats",
17731 | stan::model::index_uni(2)),
17732 | stan::model::rvalue(covmats, "covmats",
17733 | stan::model::index_uni(3)),
17734 | stan::model::rvalue(nclus, "nclus",
17735 | stan::model::index_uni(gg)),
17736 | stan::model::rvalue(cluster_size, "cluster_size",
17737 | stan::model::index_min_max(r2, (clusidx - 1))),
17738 | stan::model::rvalue(Xvar, "Xvar",
17739 | stan::model::index_uni(gg)),
17740 | stan::model::rvalue(Xbetvar, "Xbetvar",
17741 | stan::model::index_uni(gg)),
17742 | stan::model::rvalue(Nx, "Nx",
17743 | stan::model::index_uni(gg)),
17744 | stan::model::rvalue(Nx_between, "Nx_between",
17745 | stan::model::index_uni(gg)), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/elt_multiply.hpp:28:25: required from 'auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]'
28 | return m1.cwiseProduct(m2);
| ~~~~~~~~~~~~~~~^~~~
stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4497 | stan::math::elt_multiply(
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:4825:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix<double, -1, 1>; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = Eigen::Matrix<double, -1, -1>; T4__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__>, stan::is_eigen_matrix_dynamic<T4__>, stan::is_vt_not_complex<T9__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; typename stan::base_type<T9__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4825 | multi_normal_suff(
4826 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4827 | stan::model::index_multi(
4828 | stan::model::rvalue(Xvar, "Xvar",
4829 | stan::model::index_min_max(1, Nx)))),
4830 | stan::model::rvalue(cov_w, "cov_w",
4831 | stan::model::index_min_max(1, Nx),
4832 | stan::model::index_min_max(1, Nx)),
4833 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4834 | stan::model::index_multi(
4835 | stan::model::rvalue(Xvar, "Xvar",
4836 | stan::model::index_min_max(1, Nx)))),
4837 | stan::model::rvalue(cov_w_inv, "cov_w_inv",
4838 | stan::model::index_min_max(1, (Nx + 1)),
4839 | stan::model::index_min_max(1, (Nx + 1))),
4840 | stan::model::rvalue(cluster_size, "cluster_size",
4841 | stan::model::index_uni(cc)), pstream__)),
stanExports_stanmarg.h:17723:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17723 | calc_log_lik_x(
17724 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17725 | stan::model::index_min_max(r2, (clusidx - 1))),
17726 | stan::model::rvalue(mnvecs, "mnvecs",
17727 | stan::model::index_uni(2)),
17728 | stan::model::rvalue(covmats, "covmats",
17729 | stan::model::index_uni(1)),
17730 | stan::model::rvalue(covmats, "covmats",
17731 | stan::model::index_uni(2)),
17732 | stan::model::rvalue(covmats, "covmats",
17733 | stan::model::index_uni(3)),
17734 | stan::model::rvalue(nclus, "nclus",
17735 | stan::model::index_uni(gg)),
17736 | stan::model::rvalue(cluster_size, "cluster_size",
17737 | stan::model::index_min_max(r2, (clusidx - 1))),
17738 | stan::model::rvalue(Xvar, "Xvar",
17739 | stan::model::index_uni(gg)),
17740 | stan::model::rvalue(Xbetvar, "Xbetvar",
17741 | stan::model::index_uni(gg)),
17742 | stan::model::rvalue(Nx, "Nx",
17743 | stan::model::index_uni(gg)),
17744 | stan::model::rvalue(Nx_between, "Nx_between",
17745 | stan::model::index_uni(gg)), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, -1>&>(Eigen::Matrix<double, -1, -1>&, const char*, const index_multi&, index_uni)::<lambda(auto:770&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, -1>&>(Eigen::Matrix<double, -1, -1>&, const char*, const index_multi&, index_uni)::<lambda(auto:770&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, -1>&>(Eigen::Matrix<double, -1, -1>&, const char*, const index_multi&, index_uni)::<lambda(auto:770&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, -1>&>(Eigen::Matrix<double, -1, -1>&, const char*, const index_multi&, index_uni)::<lambda(auto:770&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:470:0: required from 'stan::model::rvalue<Eigen::Matrix<double, -1, -1>&>(Eigen::Matrix<double, -1, -1>&, const char*, const index_multi&, index_uni)::<lambda(auto:770&)> [with auto:770 = Eigen::Matrix<double, -1, -1>]'
469 | return Eigen::Matrix<value_type_t<EigMat>, Eigen::Dynamic, 1>::
470 | NullaryExpr(row_idx.ns_.size(),
471 | [name, &row_idx, col_i = col_idx.n_ - 1,
472 | &x_ref](Eigen::Index i) {
473 | math::check_range("matrix[multi, uni] row indexing",
474 | name, x_ref.rows(), row_idx.ns_[i]);
475 | return x_ref.coeff(row_idx.ns_[i] - 1, col_i);
476 | });
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue<Eigen::Matrix<double, -1, -1>&>(Eigen::Matrix<double, -1, -1>&, const char*, const index_multi&, index_uni)::<lambda(auto:770&)>; Args = {Eigen::Matrix<double, -1, -1, 0, -1, -1>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:467:0: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::model::rvalue(EigMat&&, const char*, const index_multi&, index_uni) [with EigMat = Eigen::Matrix<double, -1, -1>&; stan::require_eigen_dense_dynamic_t<M>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
467 | return stan::math::make_holder(
468 | [name, &row_idx, col_idx](auto& x_ref) {
469 | return Eigen::Matrix<value_type_t<EigMat>, Eigen::Dynamic, 1>::
470 | NullaryExpr(row_idx.ns_.size(),
471 | [name, &row_idx, col_i = col_idx.n_ - 1,
472 | &x_ref](Eigen::Index i) {
473 | math::check_range("matrix[multi, uni] row indexing",
474 | name, x_ref.rows(), row_idx.ns_[i]);
475 | return x_ref.coeff(row_idx.ns_[i] - 1, col_i);
476 | });
477 | },
478 | stan::math::to_ref(x));
stanExports_stanmarg.h:3204:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3204 | stan::model::rvalue(B_tilde, "B_tilde",
3205 | stan::model::index_multi(bidx), stan::model::index_uni(1))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_ldlt_factor.hpp:32:45: required from 'void stan::math::check_ldlt_factor(const char*, const char*, LDLT_factor<T>&) [with T = Eigen::Matrix<double, -1, -1>]'
32 | auto too_small = A.ldlt().vectorD().tail(1)(0);
| ~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:73:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<double, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
73 | check_ldlt_factor(function, "LDLT_Factor of random variable", ldlt_W);
stanExports_stanmarg.h:18267:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18267 | stan::math::wishart_lpdf<false>(
18268 | stan::math::multiply(
18269 | (stan::model::rvalue(N, "N", stan::model::index_uni(mm)) -
18270 | 1),
18271 | stan::model::rvalue(Sstar, "Sstar",
18272 | stan::model::index_uni(mm))),
18273 | (stan::model::rvalue(N, "N", stan::model::index_uni(mm)) -
18274 | 1),
18275 | stan::model::rvalue(Sigma, "Sigma",
18276 | stan::model::index_uni(mm))), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log<Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >(const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >&)::<lambda(const auto:169&)> [with auto:169 = Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant_ldlt.hpp:22:17: required from 'stan::value_type_t<T> stan::math::log_determinant_ldlt(LDLT_factor<T>&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_not_rev_matrix_t<T>* <anonymous> = 0; stan::value_type_t<T> = double]'
22 | return sum(log(A.ldlt().vectorD().array()));
| ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<double, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S);
stanExports_stanmarg.h:18267:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18267 | stan::math::wishart_lpdf<false>(
18268 | stan::math::multiply(
18269 | (stan::model::rvalue(N, "N", stan::model::index_uni(mm)) -
18270 | 1),
18271 | stan::model::rvalue(Sstar, "Sstar",
18272 | stan::model::index_uni(mm))),
18273 | (stan::model::rvalue(N, "N", stan::model::index_uni(mm)) -
18274 | 1),
18275 | stan::model::rvalue(Sigma, "Sigma",
18276 | stan::model::index_uni(mm))), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:24: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:268:7: required from 'Eigen::MapBase<Derived, 1>::ScalarWithConstIfNotLvalue& Eigen::MapBase<Derived, 1>::coeffRef(Eigen::Index) [with Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; ScalarWithConstIfNotLvalue = double; Eigen::Index = long long int]'
15 | EIGEN_STATIC_ASSERT((int(internal::evaluator<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:367:25: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
367 | matA.col(i).coeffRef(i+1) = 1;
| ~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:475:5: required from 'void Eigen::internal::apply_rotation_in_the_plane(Eigen::DenseBase<Derived>&, Eigen::DenseBase<Derived>&, const Eigen::JacobiRotation<OtherScalar>&) [with VectorX = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; VectorY = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; OtherScalar = double]'
475 | EIGEN_PLAIN_ENUM_MIN(evaluator<VectorX>::Alignment, evaluator<VectorY>::Alignment),
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:315:40: required from 'void Eigen::MatrixBase<Derived>::applyOnTheRight(Eigen::Index, Eigen::Index, const Eigen::JacobiRotation<OtherScalar>&) [with OtherScalar = double; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Eigen::Index = long long int]'
315 | internal::apply_rotation_in_the_plane(x, y, j.transpose());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:895:24: required from 'void Eigen::internal::tridiagonal_qr_step(RealScalar*, RealScalar*, Index, Index, Scalar*, Index) [with int StorageOrder = 0; RealScalar = double; Scalar = double; Index = long long int]'
895 | q.applyOnTheRight(k,k+1,rot);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:548:87: required from 'Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagType = Eigen::Matrix<double, -1, 1>; SubDiagType = Eigen::Matrix<double, -1, 1>; Eigen::Index = long long int]'
548 | internal::tridiagonal_qr_step<MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor>(diag.data(), subdiag.data(), start, end, computeEigenvectors ? eivec.data() : (Scalar*)0, n);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from 'static typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::internal::lpNorm_selector<Derived, 1>::run(const Eigen::MatrixBase<Derived>&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
221 | return m.cwiseAbs().sum();
| ~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
269 | return internal::lpNorm_selector<Derived, p>::run(*this);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from 'static typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::internal::lpNorm_selector<Derived, 1>::run(const Eigen::MatrixBase<Derived>&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
221 | return m.cwiseAbs().sum();
| ~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
269 | return internal::lpNorm_selector<Derived, p>::run(*this);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from 'struct Eigen::internal::evaluator_wrapper_base<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
1384 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from 'struct Eigen::internal::unary_evaluator<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>'
1464 | struct unary_evaluator<ArrayWrapper<TArgType> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:74: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from 'struct Eigen::internal::evaluator_wrapper_base<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
1384 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from 'struct Eigen::internal::unary_evaluator<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::internal::IndexBased, double>'
1464 | struct unary_evaluator<ArrayWrapper<TArgType> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:50: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
387 | ret = ret && (A21.array()==Scalar(0)).all();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Array<double, 1, -1, 1, 1, -1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Array<double, 1, -1, 1, 1, -1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Array<double, 1, -1, 1, 1, -1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Array<double, 1, -1, 1, 1, -1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Array<double, 1, -1, 1, 1, -1> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Array<double, 1, -1, 1, 1, -1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Array.h:45:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_U.hpp:44:37: required from 'void stan::math::factor_U(const T_U&, T_CPCs&&) [with T_U = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_eigen_vector_t<T_CPCs>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0]'
44 | acc.tail(pull) = 1.0 - temp.square();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > > >'
38 | >::type Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, 1, -1, 1, 1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_U.hpp:44:24: required from 'void stan::math::factor_U(const T_U&, T_CPCs&&) [with T_U = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_eigen_vector_t<T_CPCs>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0]'
44 | acc.tail(pull) = 1.0 - temp.square();
| ~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_U.hpp:49:33: required from 'void stan::math::factor_U(const T_U&, T_CPCs&&) [with T_U = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_eigen_vector_t<T_CPCs>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0]'
49 | temp /= sqrt(acc.tail(pull) / acc(i));
| ~~~~~~~~~~~~~~~^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sqrt.hpp:58:51: required from 'stan::math::sqrt<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(const auto:218&)> [with auto:218 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >]'
58 | x, [](const auto& v) { return v.array().sqrt(); });
| ~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_U.hpp:53:22: required from 'void stan::math::factor_U(const T_U&, T_CPCs&&) [with T_U = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_eigen_vector_t<T_CPCs>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0]'
53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded
| ~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_U.hpp:53:37: required from 'void stan::math::factor_U(const T_U&, T_CPCs&&) [with T_U = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_eigen_vector_t<T_CPCs>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0]'
53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded
| ~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_U.hpp:53:30: required from 'void stan::math::factor_U(const T_U&, T_CPCs&&) [with T_U = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_eigen_vector_t<T_CPCs>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0]'
53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_U.hpp:53:49: required from 'void stan::math::factor_U(const T_U&, T_CPCs&&) [with T_U = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_eigen_vector_t<T_CPCs>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0]'
53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_U.hpp:53:14: required from 'void stan::math::factor_U(const T_U&, T_CPCs&&) [with T_U = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_eigen_vector_t<T_CPCs>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0]'
53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/transpose.hpp:18:21: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/elt_multiply.hpp:28:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14525:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14525 | multi_normal_suff(
14526 | stan::model::rvalue(YXbarstar, "YXbarstar",
14527 | stan::model::index_uni(mm),
14528 | stan::model::index_multi(
14529 | stan::model::rvalue(xdatidx, "xdatidx",
14530 | stan::model::index_min_max(1,
14531 | stan::model::rvalue(Nx, "Nx",
14532 | stan::model::index_uni(mm)))))),
14533 | stan::model::rvalue(Sstar, "Sstar",
14534 | stan::model::index_uni(mm),
14535 | stan::model::index_multi(
14536 | stan::model::rvalue(xdatidx, "xdatidx",
14537 | stan::model::index_min_max(1,
14538 | stan::model::rvalue(Nx, "Nx",
14539 | stan::model::index_uni(mm))))),
14540 | stan::model::index_multi(
14541 | stan::model::rvalue(xdatidx, "xdatidx",
14542 | stan::model::index_min_max(1,
14543 | stan::model::rvalue(Nx, "Nx",
14544 | stan::model::index_uni(mm)))))),
14545 | stan::model::rvalue(Mu, "Mu",
14546 | stan::model::index_uni(grpidx),
14547 | stan::model::index_multi(
14548 | stan::model::rvalue(xidx, "xidx",
14549 | stan::model::index_min_max(1,
14550 | stan::model::rvalue(Nx, "Nx",
14551 | stan::model::index_uni(mm)))))),
14552 | sig_inv_update(
14553 | stan::model::rvalue(Sigmainv, "Sigmainv",
14554 | stan::model::index_uni(mm)), xidx,
14555 | stan::model::rvalue(Nx, "Nx",
14556 | stan::model::index_uni(mm)), (p + q),
14557 | stan::model::rvalue(logdetSigma_grp,
14558 | "logdetSigma_grp", stan::model::index_uni(grpidx)),
14559 | pstream__), ((r2 - r1) + 1), pstream__)));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/elt_multiply.hpp:28:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14525:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14525 | multi_normal_suff(
14526 | stan::model::rvalue(YXbarstar, "YXbarstar",
14527 | stan::model::index_uni(mm),
14528 | stan::model::index_multi(
14529 | stan::model::rvalue(xdatidx, "xdatidx",
14530 | stan::model::index_min_max(1,
14531 | stan::model::rvalue(Nx, "Nx",
14532 | stan::model::index_uni(mm)))))),
14533 | stan::model::rvalue(Sstar, "Sstar",
14534 | stan::model::index_uni(mm),
14535 | stan::model::index_multi(
14536 | stan::model::rvalue(xdatidx, "xdatidx",
14537 | stan::model::index_min_max(1,
14538 | stan::model::rvalue(Nx, "Nx",
14539 | stan::model::index_uni(mm))))),
14540 | stan::model::index_multi(
14541 | stan::model::rvalue(xdatidx, "xdatidx",
14542 | stan::model::index_min_max(1,
14543 | stan::model::rvalue(Nx, "Nx",
14544 | stan::model::index_uni(mm)))))),
14545 | stan::model::rvalue(Mu, "Mu",
14546 | stan::model::index_uni(grpidx),
14547 | stan::model::index_multi(
14548 | stan::model::rvalue(xidx, "xidx",
14549 | stan::model::index_min_max(1,
14550 | stan::model::rvalue(Nx, "Nx",
14551 | stan::model::index_uni(mm)))))),
14552 | sig_inv_update(
14553 | stan::model::rvalue(Sigmainv, "Sigmainv",
14554 | stan::model::index_uni(mm)), xidx,
14555 | stan::model::rvalue(Nx, "Nx",
14556 | stan::model::index_uni(mm)), (p + q),
14557 | stan::model::rvalue(logdetSigma_grp,
14558 | "logdetSigma_grp", stan::model::index_uni(grpidx)),
14559 | pstream__), ((r2 - r1) + 1), pstream__)));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:40: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma);
| ~~~~~~~^~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:50: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:50: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
94 | >= 2>(inv_sigma * y_scaled);
| ~~~~~~~~~~^~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:35: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
96 | partials<0>(ops_partials) = -scaled_diff;
| ^~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:45: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
| ~~~~~~~~~~^~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:59: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(const auto:169&)> [with auto:169 = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]'
66 | x, [](const auto& v) { return v.array().log(); });
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y);
| ~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
| ~~~~~~~~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val;
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&>(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:13&)> [with auto:13 = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >]'
57 | return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
| ~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&>(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:13&)>; Args = {const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1, 0, -1, 1> >, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1, 0, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1, 0, -1, 1> > > > >&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14695 | lp_accum__.add((stan::math::beta_lpdf<false>(
14696 | stan::math::multiply(.5,
14697 | stan::math::add(1, Theta_r_free)), theta_r_alpha,
14698 | theta_r_beta) + (stan::math::log(.5) *
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from 'static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Matrix<double, -1, 1>; U = Eigen::Matrix<double, -1, 1>; bool NeedToTranspose = false; ResScalar = double]'
37 | return a.template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Matrix<double, -1, 1>; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, std::allocator<Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value<double>; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = stan::math::var_value<double>; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
12985 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
12986 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
12987 | Psi_r_mat_1_3dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, std::allocator<Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value<double>; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = stan::math::var_value<double>; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
12985 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
12986 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
12987 | Psi_r_mat_1_3dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:32:0: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, std::allocator<Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value<double>; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = stan::math::var_value<double>; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
12985 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
12986 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
12987 | Psi_r_mat_1_3dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:510:28: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::MatrixBase<Derived>::trace() const [with Derived = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]'
510 | return derived().diagonal().sum();
| ~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/trace.hpp:26:0: required from 'auto stan::math::trace(const T&) [with T = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
26 | return make_callback_var(arena_m.val_op().trace(),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/trace_inv_quad_form_ldlt.hpp:41:0: required from 'stan::math::var stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<var_value<double>, var_value<double> >, const Eigen::Matrix<var_value<double>, -1, 1>, const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; var = var_value<double>]'
41 | auto AsolveB = to_arena(A.ldlt().solve(arena_B.val()));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/trace_inv_quad_form_ldlt.hpp:43:0: required from 'stan::math::var stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<var_value<double>, var_value<double> >, const Eigen::Matrix<var_value<double>, -1, 1>, const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; var = var_value<double>]'
43 | var res = (arena_B.val_op().transpose() * AsolveB).trace();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, 6>'
126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/trace_inv_quad_form_ldlt.hpp:46:0: required from 'stan::math::var stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<var_value<double>, var_value<double> >, const Eigen::Matrix<var_value<double>, -1, 1>, const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; var = var_value<double>]'
46 | arena_A.adj() += -res.adj() * AsolveB * AsolveB.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/trace_inv_quad_form_ldlt.hpp:55:0: required from 'stan::math::var stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<var_value<double>, var_value<double> >, const Eigen::Matrix<var_value<double>, -1, 1>, const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; var = var_value<double>]'
55 | auto AsolveB = to_arena(A.ldlt().solve(value_of(B_ref)));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/trace_inv_quad_form_ldlt.hpp:57:0: required from 'stan::math::var stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<var_value<double>, var_value<double> >, const Eigen::Matrix<var_value<double>, -1, 1>, const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; var = var_value<double>]'
57 | var res = (value_of(B_ref).transpose() * AsolveB).trace();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, 6>'
126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of_rec<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of_rec<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of_rec<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of_rec<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of_rec<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:1&)>::<lambda(auto:2)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:110:27: required from 'stan::math::value_of_rec<const Eigen::Matrix<var_value<double>, -1, -1>&>(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:1&)> [with auto:1 = const Eigen::Matrix<stan::math::var_value<double>, -1, -1>]'
110 | return m.unaryExpr([](auto x) { return value_of_rec(x); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/lkj_corr_lpdf.hpp:55:20: required from 'stan::return_type_t<T1, T2> stan::math::lkj_corr_lpdf(const T_y&, const T_shape&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, -1>; T_shape = int; stan::return_type_t<T1, T2> = var_value<double>]'
55 | check_corr_matrix(function, "Correlation matrix", y_ref);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14715:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14715 | lp_accum__.add(stan::math::lkj_corr_lpdf<false>(
14716 | stan::model::rvalue(Psi_r_mat_1,
14717 | "Psi_r_mat_1",
14718 | stan::model::index_uni(blkidx)),
14719 | stan::model::rvalue(blkse, "blkse",
14720 | stan::model::index_uni(k),
14721 | stan::model::index_uni(7))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/accumulator.hpp:135:0: required from 'stan::math::var stan::math::accumulator<T, typename std::enable_if<stan::is_var<typename std::decay<_Tp>::type>::value, void>::type>::sum() const [with T = stan::math::var_value<double>; typename std::enable_if<stan::is_var<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value<double>; stan::math::var = stan::math::var_value<double>]'
135 | inline var sum() const { return stan::math::sum(buf_); }
stanExports_stanmarg.h:14942:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14942 | return lp_accum__.sum();
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:24: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T_loc = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T_covar = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:4849:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix<double, -1, 1>; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = Eigen::Matrix<double, -1, -1>; T4__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__>, stan::is_eigen_matrix_dynamic<T4__>, stan::is_vt_not_complex<T9__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; typename stan::base_type<T9__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4849 | stan::math::multi_normal_lpdf<false>(
4850 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4851 | stan::model::index_min_max(1, Nx_between)),
4852 | stan::model::rvalue(ov_mean_d, "ov_mean_d",
4853 | stan::model::index_min_max(1, Nx_between)),
4854 | stan::model::rvalue(cov_mean_d, "cov_mean_d",
4855 | stan::model::index_min_max(1, Nx_between),
4856 | stan::model::index_min_max(1, Nx_between)))),
stanExports_stanmarg.h:17723:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17723 | calc_log_lik_x(
17724 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17725 | stan::model::index_min_max(r2, (clusidx - 1))),
17726 | stan::model::rvalue(mnvecs, "mnvecs",
17727 | stan::model::index_uni(2)),
17728 | stan::model::rvalue(covmats, "covmats",
17729 | stan::model::index_uni(1)),
17730 | stan::model::rvalue(covmats, "covmats",
17731 | stan::model::index_uni(2)),
17732 | stan::model::rvalue(covmats, "covmats",
17733 | stan::model::index_uni(3)),
17734 | stan::model::rvalue(nclus, "nclus",
17735 | stan::model::index_uni(gg)),
17736 | stan::model::rvalue(cluster_size, "cluster_size",
17737 | stan::model::index_min_max(r2, (clusidx - 1))),
17738 | stan::model::rvalue(Xvar, "Xvar",
17739 | stan::model::index_uni(gg)),
17740 | stan::model::rvalue(Xbetvar, "Xbetvar",
17741 | stan::model::index_uni(gg)),
17742 | stan::model::rvalue(Nx, "Nx",
17743 | stan::model::index_uni(gg)),
17744 | stan::model::rvalue(Nx_between, "Nx_between",
17745 | stan::model::index_uni(gg)), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1> >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_left_ldlt.hpp:37:24: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, -1, EigMat::ColsAtCompileTime> stan::math::mdivide_left_ldlt(LDLT_factor<T>&, const EigMat&) [with T = Eigen::Matrix<double, -1, -1>; EigMat = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::require_any_not_t<std::is_arithmetic<typename stan::value_type<T, void>::type>, stan::is_fvar<typename stan::value_type<T_actual, void>::type, void> >* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
37 | return A.ldlt().solve(
| ~~~~~~~~~~~~~~^
38 | Eigen::Matrix<return_type_t<T, EigMat>, EigMat::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
39 | EigMat::ColsAtCompileTime>(b));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, 4, 4>; Scalar = double]'
347 | return derived() = Constant(rows(), cols(), val);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha);
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<T>::Scalar = double]'
466 | return maxCoeff<PropagateFast>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:453:45: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
453 | RealScalar scale = mat.cwiseAbs().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:93:22: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:34:74: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:60: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:23: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive<Eigen::Matrix<var_value<double>, -1, 1> >(const char*, const char*, const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<var_value<double>, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from 'void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<var_value<double>, -1, 1>]'
29 | elementwise_check([](double x) { return x > 0; }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | "positive");
| ~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:42:17: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<var_value<double>, -1, -1>; typename stan::value_type<T>::type = var_value<double>]'
42 | check_positive("inverse_spd", "matrix not positive definite", diag_ldlt);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14139:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14139 | stan::math::inverse_spd(
14140 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:634:22: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S);
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite<Eigen::Matrix<var_value<double>, -1, 1> >(const char*, const char*, const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<var_value<double>, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from 'void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<var_value<double>, -1, 1>]'
29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | y, "finite");
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:71:17: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
71 | check_finite(function, "Location parameter", mu_vec[i]);
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::Matrix<var_value<double>, -1, 1> >(const char*, const char*, const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<var_value<double>, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<var_value<double>, -1, 1>]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:72:18: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
72 | check_not_nan(function, "Random variable", y_vec[i]);
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:510:28: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::MatrixBase<Derived>::trace() const [with Derived = Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>; typename Eigen::internal::traits<T>::Scalar = double]'
510 | return derived().diagonal().sum();
| ~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/trace_inv_quad_form_ldlt.hpp:43:0: required from 'stan::math::var stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<var_value<double>, var_value<double> >, const Eigen::Matrix<var_value<double>, -1, 1>, const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; var = var_value<double>]'
43 | var res = (arena_B.val_op().transpose() * AsolveB).trace();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:510:28: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::MatrixBase<Derived>::trace() const [with Derived = Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>; typename Eigen::internal::traits<T>::Scalar = double]'
510 | return derived().diagonal().sum();
| ~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/trace_inv_quad_form_ldlt.hpp:57:0: required from 'stan::math::var stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<var_value<double>, var_value<double> >, const Eigen::Matrix<var_value<double>, -1, 1>, const Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0; var = var_value<double>]'
57 | var res = (value_of(B_ref).transpose() * AsolveB).trace();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::Array<double, -1, 1> >(const char*, const char*, const Eigen::Array<double, -1, 1>&)::<lambda(double)>; T = Eigen::Array<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Array<double, -1, 1>]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:16: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
62 | check_not_nan(function, "Random variable", y_val);
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Array<double, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite<Eigen::Array<double, -1, 1> >(const char*, const char*, const Eigen::Array<double, -1, 1>&)::<lambda(double)>; T = Eigen::Array<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from 'void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array<double, -1, 1>]'
29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | y, "finite");
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:15: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
63 | check_finite(function, "Location parameter", mu_val);
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Array<double, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(double)>; T = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from 'void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >]'
29 | elementwise_check([](double x) { return x > 0; }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | "positive");
| ~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:17: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
64 | check_positive(function, "Scale parameter", sigma_val);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from 'void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; Matrix2 = stan::math::arena_matrix<Eigen::Matrix<double, -1, 1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0; stan::require_st_arithmetic<Op>* <anonymous> = 0; stan::math::var = stan::math::var_value<double>]'
67 | x.adj().array() += z.adj() * y.array();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:105:28: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
105 | return ops_partials.build(logp);
| ~~~~~~~~~~~~~~~~~~^~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from 'void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; Matrix2 = stan::math::arena_matrix<Eigen::Matrix<double, -1, 1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0; stan::require_st_arithmetic<Op>* <anonymous> = 0; stan::math::var = stan::math::var_value<double>]'
67 | x.adj().array() += z.adj() * y.array();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:105:28: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
105 | return ops_partials.build(logp);
| ~~~~~~~~~~~~~~~~~~^~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite<Eigen::Array<double, -1, 1> >(const char*, const char*, const Eigen::Array<double, -1, 1>&)::<lambda(double)>; T = Eigen::Array<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from 'void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array<double, -1, 1>]'
24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); },
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
25 | function, name, y, "positive finite");
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
71 | check_positive_finite(function, "Random variable", y_val);
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Array<double, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(double)>; T = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from 'void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >]'
24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); },
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
25 | function, name, y, "positive finite");
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:72:24: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
72 | check_positive_finite(function, "Shape parameter", alpha_val);
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'struct Eigen::internal::gemm_pack_rhs<double, long long int, Eigen::internal::const_blas_data_mapper<double, long long int, 1>, 4, 1, false, false>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:91:77: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
91 | gemm_pack_rhs<RhsScalar, Index, RhsMapper, Traits::nr, RhsStorageOrder> pack_rhs;
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2504 | typedef typename unpacket_traits<Packet>::half HalfPacket;
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2505 | typedef typename unpacket_traits<typename unpacket_traits<Packet>::half>::half QuarterPacket;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2508 | HalfPacketSize = unpacket_traits<HalfPacket>::size,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2509 | QuarterPacketSize = unpacket_traits<QuarterPacket>::size};
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite<Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1> >(const char*, const char*, const Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>&)::<lambda(double)>; T = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from 'void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>]'
29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | y, "finite");
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:71:17: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T_loc = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T_covar = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::return_type_t<T, L, U> = double]'
71 | check_finite(function, "Location parameter", mu_vec[i]);
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:4849:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix<double, -1, 1>; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = Eigen::Matrix<double, -1, -1>; T4__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__>, stan::is_eigen_matrix_dynamic<T4__>, stan::is_vt_not_complex<T9__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; typename stan::base_type<T9__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4849 | stan::math::multi_normal_lpdf<false>(
4850 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4851 | stan::model::index_min_max(1, Nx_between)),
4852 | stan::model::rvalue(ov_mean_d, "ov_mean_d",
4853 | stan::model::index_min_max(1, Nx_between)),
4854 | stan::model::rvalue(cov_mean_d, "cov_mean_d",
4855 | stan::model::index_min_max(1, Nx_between),
4856 | stan::model::index_min_max(1, Nx_between)))),
stanExports_stanmarg.h:17723:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17723 | calc_log_lik_x(
17724 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17725 | stan::model::index_min_max(r2, (clusidx - 1))),
17726 | stan::model::rvalue(mnvecs, "mnvecs",
17727 | stan::model::index_uni(2)),
17728 | stan::model::rvalue(covmats, "covmats",
17729 | stan::model::index_uni(1)),
17730 | stan::model::rvalue(covmats, "covmats",
17731 | stan::model::index_uni(2)),
17732 | stan::model::rvalue(covmats, "covmats",
17733 | stan::model::index_uni(3)),
17734 | stan::model::rvalue(nclus, "nclus",
17735 | stan::model::index_uni(gg)),
17736 | stan::model::rvalue(cluster_size, "cluster_size",
17737 | stan::model::index_min_max(r2, (clusidx - 1))),
17738 | stan::model::rvalue(Xvar, "Xvar",
17739 | stan::model::index_uni(gg)),
17740 | stan::model::rvalue(Xbetvar, "Xbetvar",
17741 | stan::model::index_uni(gg)),
17742 | stan::model::rvalue(Nx, "Nx",
17743 | stan::model::index_uni(gg)),
17744 | stan::model::rvalue(Nx_between, "Nx_between",
17745 | stan::model::index_uni(gg)), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1> >(const char*, const char*, const Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>&)::<lambda(double)>; T = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:72:18: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T_loc = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T_covar = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::return_type_t<T, L, U> = double]'
72 | check_not_nan(function, "Random variable", y_vec[i]);
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:4849:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix<double, -1, 1>; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = Eigen::Matrix<double, -1, -1>; T4__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__>, stan::is_eigen_matrix_dynamic<T4__>, stan::is_vt_not_complex<T9__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; typename stan::base_type<T9__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4849 | stan::math::multi_normal_lpdf<false>(
4850 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4851 | stan::model::index_min_max(1, Nx_between)),
4852 | stan::model::rvalue(ov_mean_d, "ov_mean_d",
4853 | stan::model::index_min_max(1, Nx_between)),
4854 | stan::model::rvalue(cov_mean_d, "cov_mean_d",
4855 | stan::model::index_min_max(1, Nx_between),
4856 | stan::model::index_min_max(1, Nx_between)))),
stanExports_stanmarg.h:17723:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17723 | calc_log_lik_x(
17724 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17725 | stan::model::index_min_max(r2, (clusidx - 1))),
17726 | stan::model::rvalue(mnvecs, "mnvecs",
17727 | stan::model::index_uni(2)),
17728 | stan::model::rvalue(covmats, "covmats",
17729 | stan::model::index_uni(1)),
17730 | stan::model::rvalue(covmats, "covmats",
17731 | stan::model::index_uni(2)),
17732 | stan::model::rvalue(covmats, "covmats",
17733 | stan::model::index_uni(3)),
17734 | stan::model::rvalue(nclus, "nclus",
17735 | stan::model::index_uni(gg)),
17736 | stan::model::rvalue(cluster_size, "cluster_size",
17737 | stan::model::index_min_max(r2, (clusidx - 1))),
17738 | stan::model::rvalue(Xvar, "Xvar",
17739 | stan::model::index_uni(gg)),
17740 | stan::model::rvalue(Xbetvar, "Xbetvar",
17741 | stan::model::index_uni(gg)),
17742 | stan::model::rvalue(Nx, "Nx",
17743 | stan::model::index_uni(gg)),
17744 | stan::model::rvalue(Nx_between, "Nx_between",
17745 | stan::model::index_uni(gg)), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:142:7: required from 'Eigen::DenseCoeffsBase<Derived, 0>::CoeffReturnType Eigen::DenseCoeffsBase<Derived, 0>::coeff(Eigen::Index) const [with Derived = Eigen::Block<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>; CoeffReturnType = double; Eigen::Index = long long int]'
142 | EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:182:19: required from 'Eigen::DenseCoeffsBase<Derived, 0>::CoeffReturnType Eigen::DenseCoeffsBase<Derived, 0>::operator()(Eigen::Index) const [with Derived = Eigen::Block<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>; CoeffReturnType = double; Eigen::Index = long long int]'
182 | return coeff(index);
| ~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_ldlt_factor.hpp:32:48: required from 'void stan::math::check_ldlt_factor(const char*, const char*, LDLT_factor<T>&) [with T = Eigen::Matrix<double, -1, -1>]'
32 | auto too_small = A.ldlt().vectorD().tail(1)(0);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:73:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<double, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
73 | check_ldlt_factor(function, "LDLT_Factor of random variable", ldlt_W);
stanExports_stanmarg.h:18267:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18267 | stan::math::wishart_lpdf<false>(
18268 | stan::math::multiply(
18269 | (stan::model::rvalue(N, "N", stan::model::index_uni(mm)) -
18270 | 1),
18271 | stan::model::rvalue(Sstar, "Sstar",
18272 | stan::model::index_uni(mm))),
18273 | (stan::model::rvalue(N, "N", stan::model::index_uni(mm)) -
18274 | 1),
18275 | stan::model::rvalue(Sigma, "Sigma",
18276 | stan::model::index_uni(mm))), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from 'ResultType Eigen::internal::member_sum<ResultType, Scalar>::operator()(const XprType&) const [with XprType = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; ResultType = double; Scalar = double]'
97 | { return mat.MEMBER(); } \
| ~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from 'const Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::Scalar Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; int Direction = 1; Scalar = double; Eigen::Index = long long int]'
183 | return m_functor(m_arg.template subVector<DirectionType(Direction)>(index));
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >; Scalar = double]'
268 | res = func(res,eval.coeff(index));
| ~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]'
466 | return maxCoeff<PropagateFast>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here
106 | return x.cwiseAbs().rowwise().sum().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, 1>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >'
1043 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>'
564 | CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
269 | return internal::lpNorm_selector<Derived, p>::run(*this);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>'
564 | CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
269 | return internal::lpNorm_selector<Derived, p>::run(*this);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::internal::IndexBased, double>'
564 | CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from 'class Eigen::internal::visitor_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> > >'
79 | CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from 'void Eigen::DenseBase<Derived>::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >]'
123 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:54: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:46: required from 'stan::math::matrix_d stan::math::multiply_lower_tri_self_transpose(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_matrix_dynamic_t<EigMat>* <anonymous> = 0; stan::require_not_st_autodiff<EigMat>* <anonymous> = 0; matrix_d = Eigen::Matrix<double, -1, -1>]'
35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t<T>&) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >; Functor = mul_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >; Functor = Eigen::internal::mul_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >; Func = mul_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >; Func = mul_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:207:18: required from 'Derived& Eigen::ArrayBase<Derived>::operator*=(const Eigen::ArrayBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >; Derived = Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>]'
207 | call_assignment(derived(), other.derived(), internal::mul_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:69:20: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_L(const T&, size_t) [with T = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int]'
69 | acc.tail(pull) *= T_scalar(1.0) - temp.square();
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:32:55: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int]'
32 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:45:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int]'
45 | return read_corr_matrix(corr_constrain(x), k);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:949:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
949 | return corr_matrix_constrain(
950 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
951 | k);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:16: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
62 | check_not_nan(function, "Random variable", y_val);
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from 'void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]'
29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
30 | y, "finite");
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:15: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
63 | check_finite(function, "Location parameter", mu_val);
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from 'void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]'
24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); },
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
25 | function, name, y, "positive finite");
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
71 | check_positive_finite(function, "Random variable", y_val);
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::EigenBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >::Index' {aka 'long long int'} [-Wsign-compare]
153 | for (size_t i = 0; i < x.size(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:25:0: required from 'void stan::math::internal::quad_form_vari_alloc<Ta, Ra, Ca, Tb, Rb, Cb>::compute(const Eigen::Matrix<double, R1, C1>&, const Eigen::Matrix<double, Rb, Cb>&) [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
25 | matrix_d M = 0.5 * (Cd + Cd.transpose());
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:40:0: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form_sym.hpp:37:0: required from 'auto stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<var_value<double>, -1, -1>; EigMat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_any_vt_var<EigMat1, EigMat2>* <anonymous> = 0]'
37 | return quad_form(A_ref, B, true);
stanExports_stanmarg.h:13579:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13579 | stan::math::quad_form_sym(
13580 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
13581 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of 'void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan<Eigen::Matrix<var_value<double>, -1, -1> >(const char*, const char*, const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(double)>; T = Eigen::Matrix<var_value<double>, -1, -1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* <anonymous> = 0]':
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from 'void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix<var_value<double>, -1, -1>]'
28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y,
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
29 | "not nan");
| ~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:161:0: required from 'Eigen::Matrix<stan::math::var_value<double>, EigMat1::RowsAtCompileTime, EigMat2::ColsAtCompileTime> stan::math::mdivide_left_spd(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<var_value<double>, -1, -1>; EigMat2 = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_all_eigen_matrix_base_vt<stan::is_var, EigMat1, EigMat2>* <anonymous> = 0]'
161 | check_not_nan(function, "A", A_ref);
stanExports_stanmarg.h:4445:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:207:24: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::Index' {aka 'long long int'} [-Wsign-compare]
207 | for (size_t i = 0; i < x.rows(); i++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:208:26: warning: comparison of integer expressions of different signedness: 'size_t' {aka 'long long unsigned int'} and 'Eigen::Index' {aka 'long long int'} [-Wsign-compare]
208 | for (size_t j = 0; j < x.cols(); j++) {
| ~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533:30: required from 'void Eigen::PartialPivLU<MatrixType>::compute() [with _MatrixType = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
533 | m_l1_norm = m_lu.cwiseAbs().colwise().sum().maxCoeff();
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:133:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from 'class Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>'
56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type,
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533:46: required from 'void Eigen::PartialPivLU<MatrixType>::compute() [with _MatrixType = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
533 | m_l1_norm = m_lu.cwiseAbs().colwise().sum().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:133:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:478:32: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::mean() const [with Derived = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits<T>::Scalar = double]'
478 | return Scalar(derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>())) / Scalar(this->size());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mean.hpp:25:73: required from 'stan::math::mean<std::vector<double> >(const std::vector<double>&)::<lambda(const auto:229&)> [with auto:229 = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
25 | [](const auto& a) { return a.mean(); });
| ~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::mean<std::vector<double> >(const std::vector<double>&)::<lambda(const auto:229&)>; T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
93 | return f(x);
| ~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:158:45: required from 'static auto stan::math::apply_vector_unary<T, typename std::enable_if<std::integral_constant<bool, stan::math::conjunction<stan::is_std_vector<typename std::decay<_Tp>::type, void>, stan::is_stan_scalar<typename stan::value_type<T, void>::type> >::value>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::mean<std::vector<double> >(const std::vector<double>&)::<lambda(const auto:229&)>; T = std::vector<double>]'
158 | return apply_vector_unary<T_map>::reduce(as_column_vector_or_scalar(x), f);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mean.hpp:24:39: required from 'stan::return_type_t<T> stan::math::mean(const T&) [with T = std::vector<double>; stan::require_container_t<T>* <anonymous> = 0; stan::return_type_t<T> = double]'
24 | return apply_vector_unary<T>::reduce(m,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
25 | [](const auto& a) { return a.mean(); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17288:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17288 | stan::math::mean(
17289 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17290 | stan::model::index_min_max(r1, ((r1 +
17291 | stan::model::rvalue(cluster_size, "cluster_size",
17292 | stan::model::index_uni(clusidx))) - 1)),
17293 | stan::model::index_uni(jj))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, Packet, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::const_blas_data_mapper<double, long long int, 0>; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:106:17: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [with Index = long long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]'
106 | pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]'
109 | internal::general_matrix_matrix_triangular_product<Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
110 | Scalar, OtherIsRowMajor ? RowMajor : ColMajor, OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
113 | ::run(size, depth,
| ~~~~~^~~~~~~~~~~~~
114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]'
126 | selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
33 | return result.setZero().template selfadjointView<Eigen::Upper>().rankUpdate(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
34 | M_ref);
| ~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2100 | typedef typename unpacket_traits<typename unpacket_traits<Packet>::half>::half QuarterPacket;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2102 | HalfPacketSize = unpacket_traits<HalfPacket>::size,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2103 | QuarterPacketSize = unpacket_traits<QuarterPacket>::size,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4496:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T3__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4496 | ((stan::math::sum(
4497 | stan::math::elt_multiply(
4498 | stan::model::rvalue(Supdate, "Supdate",
4499 | stan::model::index_min_max(1, Nobs),
4500 | stan::model::index_min_max(1, Nobs)),
4501 | stan::math::add(S,
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:4825:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix<double, -1, 1>; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = Eigen::Matrix<double, -1, -1>; T4__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__>, stan::is_eigen_matrix_dynamic<T4__>, stan::is_vt_not_complex<T9__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; typename stan::base_type<T9__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4825 | multi_normal_suff(
4826 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4827 | stan::model::index_multi(
4828 | stan::model::rvalue(Xvar, "Xvar",
4829 | stan::model::index_min_max(1, Nx)))),
4830 | stan::model::rvalue(cov_w, "cov_w",
4831 | stan::model::index_min_max(1, Nx),
4832 | stan::model::index_min_max(1, Nx)),
4833 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4834 | stan::model::index_multi(
4835 | stan::model::rvalue(Xvar, "Xvar",
4836 | stan::model::index_min_max(1, Nx)))),
4837 | stan::model::rvalue(cov_w_inv, "cov_w_inv",
4838 | stan::model::index_min_max(1, (Nx + 1)),
4839 | stan::model::index_min_max(1, (Nx + 1))),
4840 | stan::model::rvalue(cluster_size, "cluster_size",
4841 | stan::model::index_uni(cc)), pstream__)),
stanExports_stanmarg.h:17723:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17723 | calc_log_lik_x(
17724 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17725 | stan::model::index_min_max(r2, (clusidx - 1))),
17726 | stan::model::rvalue(mnvecs, "mnvecs",
17727 | stan::model::index_uni(2)),
17728 | stan::model::rvalue(covmats, "covmats",
17729 | stan::model::index_uni(1)),
17730 | stan::model::rvalue(covmats, "covmats",
17731 | stan::model::index_uni(2)),
17732 | stan::model::rvalue(covmats, "covmats",
17733 | stan::model::index_uni(3)),
17734 | stan::model::rvalue(nclus, "nclus",
17735 | stan::model::index_uni(gg)),
17736 | stan::model::rvalue(cluster_size, "cluster_size",
17737 | stan::model::index_min_max(r2, (clusidx - 1))),
17738 | stan::model::rvalue(Xvar, "Xvar",
17739 | stan::model::index_uni(gg)),
17740 | stan::model::rvalue(Xbetvar, "Xbetvar",
17741 | stan::model::index_uni(gg)),
17742 | stan::model::rvalue(Nx, "Nx",
17743 | stan::model::index_uni(gg)),
17744 | stan::model::rvalue(Nx_between, "Nx_between",
17745 | stan::model::index_uni(gg)), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Functor = assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>]'
836 | call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from 'Derived& Eigen::MatrixBase<Derived>::operator=(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Derived = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
66 | internal::call_assignment(derived(), other.derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from 'int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
72 | Eigen::Map<Eigen::VectorXd>(&row[0], draws.cols()) = draws.row(i);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1253:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::standalone_gqs(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1253 | ret = stan::services::standalone_generate(model_, draws,
1254 | Rcpp::as<unsigned int>(seed), interrupt, logger, *sample_writer_ptr);
stanExports_stanmarg.cc:30:0: required from here
30 | .method("standalone_gqs", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::standalone_gqs)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase<Derived>::_init1(const Eigen::DenseBase<ElseDerived>&) [with T = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
883 | this->_set_noalias(other);
| ~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
332 | Base::template _init1<T>(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::Matrix<double, -1, -1>; Src = Eigen::Product<Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Func = add_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
850 | typename plain_matrix_type<Src>::type tmp(src);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
177 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here
28 | m2_ += (q - m_) * delta.transpose();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:280:48: required from 'void Eigen::internal::outer_product_selector_run(Dst&, const Lhs&, const Rhs&, const Func&, const false_type&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, 1> >; Func = generic_product_impl<Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, Eigen::DenseShape, Eigen::DenseShape, 5>::set]'
280 | func(dst.col(j), rhsEval.coeff(Index(0),j) * actual_lhs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:317:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase<Derived>::_init1(const Eigen::DenseBase<ElseDerived>&) [with T = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
883 | this->_set_noalias(other);
| ~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
332 | Base::template _init1<T>(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::Matrix<double, -1, -1>; Src = Eigen::Product<Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Func = add_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
850 | typename plain_matrix_type<Src>::type tmp(src);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
177 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here
28 | m2_ += (q - m_) * delta.transpose();
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:333:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of 'class Eigen::internal::gemv_traits<double, double, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:306:38: required from 'struct Eigen::internal::general_matrix_vector_product<long long int, double, Eigen::internal::const_blas_data_mapper<double, long long int, 1>, 1, false, double, Eigen::internal::const_blas_data_mapper<double, long long int, 0>, false, 0>'
306 | typedef typename Traits::LhsPacket LhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from 'static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Dest = Eigen::Matrix<double, -1, 1>; typename Dest::Scalar = double]'
346 | general_matrix_vector_product
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
347 | <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
348 | actualLhs.rows(), actualLhs.cols(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
350 | RhsMapper(actualRhsPtr, 1),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~
351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
352 | actualAlpha);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 7>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Scalar = double]'
385 | internal::gemv_dense_selector<Side,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
386 | (int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
387 | bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
388 | >::run(actual_lhs, actual_rhs, dst, alpha);
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]'
361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
| ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, Eigen::DenseShape, Eigen::DenseShape, 7>]'
349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable &&
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
52 | unpacket_traits<_RhsPacket>::vectorizable &&
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size),
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size),
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
59 | typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
60 | typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
61 | typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of 'class Eigen::internal::gemv_traits<double, double, 1>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:310:42: required from 'struct Eigen::internal::general_matrix_vector_product<long long int, double, Eigen::internal::const_blas_data_mapper<double, long long int, 1>, 1, false, double, Eigen::internal::const_blas_data_mapper<double, long long int, 0>, false, 0>'
310 | typedef typename HalfTraits::LhsPacket LhsPacketHalf;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from 'static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Dest = Eigen::Matrix<double, -1, 1>; typename Dest::Scalar = double]'
346 | general_matrix_vector_product
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
347 | <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
348 | actualLhs.rows(), actualLhs.cols(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
350 | RhsMapper(actualRhsPtr, 1),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~
351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
352 | actualAlpha);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 7>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Scalar = double]'
385 | internal::gemv_dense_selector<Side,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
386 | (int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
387 | bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
388 | >::run(actual_lhs, actual_rhs, dst, alpha);
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]'
361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
| ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, Eigen::DenseShape, Eigen::DenseShape, 7>]'
349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable &&
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
52 | unpacket_traits<_RhsPacket>::vectorizable &&
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size),
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size),
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
59 | typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
60 | typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
61 | typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of 'class Eigen::internal::gemv_traits<double, double, 2>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:314:45: required from 'struct Eigen::internal::general_matrix_vector_product<long long int, double, Eigen::internal::const_blas_data_mapper<double, long long int, 1>, 1, false, double, Eigen::internal::const_blas_data_mapper<double, long long int, 0>, false, 0>'
314 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from 'static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Dest = Eigen::Matrix<double, -1, 1>; typename Dest::Scalar = double]'
346 | general_matrix_vector_product
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
347 | <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
348 | actualLhs.rows(), actualLhs.cols(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
350 | RhsMapper(actualRhsPtr, 1),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~
351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
352 | actualAlpha);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 7>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Scalar = double]'
385 | internal::gemv_dense_selector<Side,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
386 | (int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
387 | bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
388 | >::run(actual_lhs, actual_rhs, dst, alpha);
| ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]'
361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
| ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, Eigen::DenseShape, Eigen::DenseShape, 7>]'
349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize);
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro 'PACKET_DECL_COND_PREFIX'
42 | prefix ## name ## Packet
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable &&
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
52 | unpacket_traits<_RhsPacket>::vectorizable &&
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size),
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size),
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
59 | typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
60 | typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
61 | typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from 'static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; U = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]'
37 | return a.template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:37:52: required from 'stan::math::matrix_d stan::math::multiply_lower_tri_self_transpose(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_matrix_dynamic_t<EigMat>* <anonymous> = 0; stan::require_not_st_autodiff<EigMat>* <anonymous> = 0; matrix_d = Eigen::Matrix<double, -1, -1>]'
37 | LLt(n, m) = LLt(m, n) = Lt.col(m).head(k).dot(Lt.col(n).head(k));
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t<T>&) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Array<double, 1, -1, 1, 1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Array<double, 1, -1, 1, 1, -1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Array<double, 1, -1, 1, 1, -1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Array<double, 1, -1, 1, 1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Transpose<Eigen::Array<double, 1, -1, 1, 1, -1> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Array<double, 1, -1, 1, 1, -1>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Transpose<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Matrix<double, -1, 1> > >, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 6>'
126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:29:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1626:36: required from 'struct Eigen::internal::evaluator<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
1626 | typedef typename XprType::Scalar Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:65:8: required from 'struct Eigen::internal::evaluator<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0> >'
65 | struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 6>'
126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:29:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1626:36: required from 'struct Eigen::internal::evaluator<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >'
1626 | typedef typename XprType::Scalar Scalar;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:65:8: required from 'struct Eigen::internal::evaluator<Eigen::Diagonal<const Eigen::Product<Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, 0> >'
65 | struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:129:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:129:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:131:25: required from 'void Eigen::MatrixBase<Derived>::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Scalar = double]'
131 | this->row(0) -= tau * tmp;
| ~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:550:35: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:132:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
stanExports_stanmarg.h:4337:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4337 | stan::math::sum(
4338 | stan::model::rvalue(YXfull, "YXfull",
4339 | stan::model::index_min_max(r1, r2), stan::model::index_uni(i)))),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3419 | q_zz = stan::math::sum(stan::math::elt_multiply(Vinv_11, Y2Yc_zz));
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:53: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>; SrcXprType = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Functor = assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>; SrcXprType = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>; Src = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>; Src = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>; Src = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
836 | call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from 'Eigen::CommaInitializer<Derived> Eigen::DenseBase<Derived>::operator<<(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix<double, -1, 1>]'
159 | return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t<stan::is_eigen_col_vector<T> >* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
102 | result << A.template cast<T_return>(), B;
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from 'T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0);
| ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from 'auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 0]'
123 | return internal::hypergeometric_3F2_infsum(a, b, z);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from 'auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t<Ta, Tb, Tz>* <anonymous> = 0]'
148 | return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(b), z);
| ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here
77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w))
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>'
564 | CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:221:28: required from 'static typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::internal::lpNorm_selector<Derived, 1>::run(const Eigen::MatrixBase<Derived>&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
221 | return m.cwiseAbs().sum();
| ~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
269 | return internal::lpNorm_selector<Derived, p>::run(*this);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; Rhs = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:56: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from 'static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Matrix<double, -1, 1>; U = Eigen::Matrix<double, -1, 1>; bool NeedToTranspose = false; ResScalar = double]'
37 | return a.template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Matrix<double, -1, 1>; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1,
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/accumulator.hpp:73:0: required from 'void stan::math::accumulator<T, typename std::enable_if<stan::is_var<typename std::decay<_Tp>::type>::value, void>::type>::add(const S&) [with S = Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; stan::require_matrix_t<S>* <anonymous> = 0; T = stan::math::var_value<double>; typename std::enable_if<stan::is_var<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value<double>]'
73 | buf_.push_back(stan::math::sum(m));
stanExports_stanmarg.h:14316:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14316 | lp_accum__.add(stan::math::minus(log_lik_x));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:38: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
82 | T_partials_return logp = -0.5 * sum(y_scaled_sq);
| ~~~^~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:16: required from 'stan::return_type_t<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
87 | logp -= sum(log(sigma_val)) * N / math::size(sigma);
| ~~~^~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14607 | lp_accum__.add(stan::math::normal_lpdf<false>(Lambda_y_free,
14608 | lambda_y_primn, lambda_y_sd));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:16: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
100 | logp += sum(alpha_val * log_beta) * N / max_size(alpha, beta);
| ~~~^~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:16: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
106 | logp += sum((alpha_val - 1.0) * log_y) * N / max_size(alpha, y);
| ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y);
| ~~~^~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<-1, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<-1, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<-1, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<-1, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<-1, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<-1, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >::match<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false> >'
44 | DerivedAlignment = int(evaluator<Derived>::Alignment),
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Ref.h:288:101: required by substitution of 'template<class Derived> Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >::Ref(const Eigen::DenseBase<Derived>&, typename Eigen::internal::enable_if<(bool)(Eigen::internal::traits<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >::match<Derived>::MatchAtCompileTime), Derived>::type*) [with Derived = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>]'
288 | typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0);
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:463:17: required from 'static Eigen::Index Eigen::internal::partial_lu_impl<Scalar, StorageOrder, PivIndex, SizeAtCompileTime>::blocked_lu(Eigen::Index, Eigen::Index, Scalar*, Eigen::Index, PivIndex*, PivIndex&, Eigen::Index) [with Scalar = double; int StorageOrder = 1; PivIndex = int; int SizeAtCompileTime = -1; Eigen::Index = long long int]'
463 | BlockType A_0 = lu.block(0,0,rows,k);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:519:17: required from 'void Eigen::internal::partial_lu_inplace(MatrixType&, TranspositionType&, typename TranspositionType::StorageIndex&) [with MatrixType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; typename TranspositionType::StorageIndex = int]'
515 | partial_lu_impl
| ~~~~~~~~~~~~~~~
516 | < typename MatrixType::Scalar, MatrixType::Flags&RowMajorBit?RowMajor:ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
517 | typename TranspositionType::StorageIndex,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
518 | EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime)>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
519 | ::blocked_lu(lu.rows(), lu.cols(), &lu.coeffRef(0,0), lu.outerStride(), &row_transpositions.coeffRef(0), nb_transpositions);
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:543:31: required from 'void Eigen::PartialPivLU<MatrixType>::compute() [with _MatrixType = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
543 | internal::partial_lu_inplace(m_lu, m_rowsTranspositions, nb_transpositions);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:133:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:495:30: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:110:23: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:58: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::Matrix<double, -1, 1>; Functor = assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::Matrix<double, -1, 1>; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; Src = Eigen::Matrix<double, -1, 1>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; Src = Eigen::Matrix<double, -1, 1>; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/append_col.hpp:49:26: required from 'auto stan::math::append_col(const T1&, const T2&) [with T1 = Eigen::Matrix<double, -1, 1>; T2 = Eigen::Matrix<double, -1, -1>; <template-parameter-1-3> = void]'
49 | result.leftCols(Acols) = A.template cast<T_return>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:2847:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type>::type, -1, -1> model_stanmarg_namespace::calc_B_tilde(const T0__&, const T1__&, const std::vector<int>&, const int&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T1__ = Eigen::Matrix<double, -1, 1>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type>::type = double; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; std::ostream = std::basic_ostream<char>]'
2847 | stan::model::assign(out, stan::math::append_col(mu2, sig2),
stanExports_stanmarg.h:17229:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17229 | calc_B_tilde(
17230 | stan::model::rvalue(Sigma_c, "Sigma_c",
17231 | stan::model::index_uni(gg)), YXstar_rep_c, ov_idx2,
17232 | p_tilde, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:53: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T_loc = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T_covar = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:4849:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix<double, -1, 1>; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = Eigen::Matrix<double, -1, -1>; T4__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_col_vector<Col>, stan::is_vt_not_complex<T1__>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__>, stan::is_eigen_matrix_dynamic<T4__>, stan::is_vt_not_complex<T9__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type, typename stan::base_type<T9__, void>::type>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T3__, void>::type = double; typename stan::base_type<T9__, void>::type = double; std::ostream = std::basic_ostream<char>]'
4849 | stan::math::multi_normal_lpdf<false>(
4850 | stan::model::rvalue(mean_d, "mean_d", stan::model::index_uni(cc),
4851 | stan::model::index_min_max(1, Nx_between)),
4852 | stan::model::rvalue(ov_mean_d, "ov_mean_d",
4853 | stan::model::index_min_max(1, Nx_between)),
4854 | stan::model::rvalue(cov_mean_d, "cov_mean_d",
4855 | stan::model::index_min_max(1, Nx_between),
4856 | stan::model::index_min_max(1, Nx_between)))),
stanExports_stanmarg.h:17723:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17723 | calc_log_lik_x(
17724 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17725 | stan::model::index_min_max(r2, (clusidx - 1))),
17726 | stan::model::rvalue(mnvecs, "mnvecs",
17727 | stan::model::index_uni(2)),
17728 | stan::model::rvalue(covmats, "covmats",
17729 | stan::model::index_uni(1)),
17730 | stan::model::rvalue(covmats, "covmats",
17731 | stan::model::index_uni(2)),
17732 | stan::model::rvalue(covmats, "covmats",
17733 | stan::model::index_uni(3)),
17734 | stan::model::rvalue(nclus, "nclus",
17735 | stan::model::index_uni(gg)),
17736 | stan::model::rvalue(cluster_size, "cluster_size",
17737 | stan::model::index_min_max(r2, (clusidx - 1))),
17738 | stan::model::rvalue(Xvar, "Xvar",
17739 | stan::model::index_uni(gg)),
17740 | stan::model::rvalue(Xbetvar, "Xbetvar",
17741 | stan::model::index_uni(gg)),
17742 | stan::model::rvalue(Nx, "Nx",
17743 | stan::model::index_uni(gg)),
17744 | stan::model::rvalue(Nx_between, "Nx_between",
17745 | stan::model::index_uni(gg)), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:166:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
370 | * (conj(h) * matA.col(i).tail(remainingSize)));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from 'static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; U = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]'
37 | return a.template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
361 | A21.noalias() -= A20 * temp.head(k);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
361 | A21.noalias() -= A20 * temp.head(k);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, -1, 1>; SrcXprType = Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false>; Functor = assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, -1, 1>; SrcXprType = Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false>; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Array<double, -1, 1>; Src = Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Array<double, -1, 1>; Src = Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false>; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Array<double, -1, 1>; Src = Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<1> >, -1, 1, false>]'
836 | call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:126:21: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_L(const T&, size_t, stan::value_type_t<T>&) [with T = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
126 | return read_corr_L(CPCs_ref, K);
| ~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:55: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t<T>&) [with T_CPCs = Eigen::Matrix<double, -1, 1>; stan::require_eigen_vector_t<C>* <anonymous> = 0; typename stan::value_type<T>::type = double; size_t = long long unsigned int; stan::value_type_t<T> = double]'
61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t<T>&) [with T = Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t<T>* <anonymous> = 0; typename stan::value_type<T>::type = double; Eigen::Index = long long int; stan::return_type_t<T> = double]'
74 | return read_corr_matrix(corr_constrain(x, lp), k, lp);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix<double, -1, -1>; bool Jacobian = false; LP = double; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; stan::require_matrix_t<S>* <anonymous> = 0; T = double; Eigen::Index = long long int]'
945 | return corr_matrix_constrain(
946 | this->read<conditional_var_val_t<Ret, vector_t>>((k * (k - 1)) / 2),
947 | k, lp);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<double, -1, -1> >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:15015:0: required from here
15013 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
15014 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
15016 | Psi_r_mat_1_3dim__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
47 | return m.sum();
| ~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from 'stan::return_type_t<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = std::vector<double>; T_inv_scale = std::vector<double>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y);
| ~~~^~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]'
14689 | lp_accum__.add(stan::math::gamma_lpdf<false>(Theta_pri,
14690 | theta_sd_shape, theta_sd_rate));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from 'int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
56 | lp = model.template log_prob<false, jacobian>(cont_vector, disc_vector,
57 | &message);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
502 | = stan::services::optimize::newton(model, *init_context_ptr,
503 | random_seed, id, init_radius,
504 | num_iterations,
505 | save_iterations,
506 | interrupt, logger,
507 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:72: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:55: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 3>::eval_dynamic_impl(Dst&, const LhsT&, const RhsT&, const Func&, const Scalar&, Eigen::internal::true_type) [with Dst = Eigen::Matrix<double, -1, -1>; LhsT = Eigen::Matrix<double, -1, -1>; RhsT = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Func = Eigen::internal::assign_op<double, double>; Scalar = double; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]'
469 | call_restricted_packet_assignment_no_alias(dst, s * lhs.lazyProduct(rhs), func);
| ~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:446:22: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:377:43: required from 'static Eigen::Index Eigen::internal::partial_lu_impl<Scalar, StorageOrder, PivIndex, SizeAtCompileTime>::unblocked_lu(MatrixTypeRef&, PivIndex*, PivIndex&) [with Scalar = double; int StorageOrder = 1; PivIndex = int; int SizeAtCompileTime = -1; Eigen::Index = long long int; MatrixTypeRef = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >]'
377 | = lu.col(k).tail(rows-k).unaryExpr(Scoring()).maxCoeff(&row_of_biggest_in_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:439:26: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:400:114: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:44:20: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; typename stan::value_type<T>::type = double]'
44 | return ldlt.solve(
| ~~~~~~~~~~^
45 | Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>::Identity(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
46 | m.rows(), m.cols()));
| ~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:16304:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16304 | stan::math::inverse_spd(
16305 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, -1>, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, -1>, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, -1>, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, -1>, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, -1>, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, -1>, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:610:38: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:44:20: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; typename stan::value_type<T>::type = double]'
44 | return ldlt.solve(
| ~~~~~~~~~~^
45 | Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>::Identity(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
46 | m.rows(), m.cols()));
| ~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:16304:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16304 | stan::math::inverse_spd(
16305 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from 'class Eigen::internal::visitor_evaluator<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false> >'
79 | CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from 'void Eigen::DenseBase<Derived>::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor<Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false>, 0>; Derived = Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false>]'
123 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff(IndexType*) const [with int NaNPropagation = 0; IndexType = long long int; Derived = Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false>; typename Eigen::internal::traits<T>::Scalar = double]'
374 | this->visit(maxVisitor);
| ~~~~~~~~~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:501:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff(IndexType*) const [with IndexType = long long int; Derived = Eigen::Block<Eigen::Matrix<double, 1, -1>, 1, -1, false>; typename Eigen::internal::traits<T>::Scalar = double]'
501 | return maxCoeff<PropagateFast>(index);
| ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:521:90: required from 'void Eigen::ColPivHouseholderQR<MatrixType>::computeInPlace() [with _MatrixType = Eigen::Matrix<double, -1, -1>]'
521 | RealScalar biggest_col_sq_norm = numext::abs2(m_colNormsUpdated.tail(cols-k).maxCoeff(&biggest_col_index));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:477:3: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >; Functor = assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/access_helpers.hpp:92:0: required from 'void stan::model::internal::assign_impl(T1&&, T2&&, const char*) [with T1 = Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>; T2 = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >&; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0]'
92 | x = std::forward<T2>(y);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:141:0: required from 'void stan::model::assign(Vec1&&, const Vec2&, const char*, index_min_max) [with Vec1 = Eigen::Matrix<double, -1, 1>&; Vec2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_all_not_std_vector_t<T1, T2>* <anonymous> = 0]'
141 | internal::assign_impl(x.segment(slice_start, slice_size), y, name);
stanExports_stanmarg.h:18213:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18213 | stan::model::assign(log_lik,
18214 | stan::math::subtract(
18215 | stan::model::deep_copy(
18216 | stan::model::rvalue(log_lik, "log_lik",
18217 | stan::model::index_min_max(r1, r2))),
18218 | stan::model::rvalue(log_lik_x_full, "log_lik_x_full",
18219 | stan::model::index_min_max(r1, r2))),
18220 | "assigning variable log_lik",
18221 | stan::model::index_min_max(r1, r2));
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
370 | * (conj(h) * matA.col(i).tail(remainingSize)));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1));
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:40: required from 'static void Eigen::internal::gemv_dense_selector<2, 0, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Rhs = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>; typename Dest::Scalar = double]'
296 | dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size());
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
361 | A21.noalias() -= A20 * temp.head(k);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false> >'
1043 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, 1, -1, 1, 1, -1>; SrcXprType = Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Functor = assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, 1, -1, 1, 1, -1>; SrcXprType = Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Array<double, 1, -1, 1, 1, -1>; Src = Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, 1, -1, 1, 1, -1>; SrcXprType = Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Functor = assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, 1, -1, 1, 1, -1>; SrcXprType = Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Array<double, 1, -1, 1, 1, -1>; Src = Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Derived = Eigen::Array<double, 1, -1, 1, 1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::Block<const Eigen::Ref<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Derived = Eigen::Array<double, 1, -1, 1, 1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Array.h:288:29: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >; SrcXprType = Eigen::Array<double, 1, -1, 1, 1, -1>; Functor = assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false> >; SrcXprType = Eigen::Array<double, 1, -1, 1, 1, -1>; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, -1, 1, false>; Src = Eigen::Array<double, 1, -1, 1, 1, -1>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/factor_cov_matrix.hpp:51:11: required from 'bool stan::math::factor_cov_matrix(const T_Sigma&, T_CPCs&&, T_sds&&) [with T_Sigma = Eigen::Matrix<double, -1, -1>; T_CPCs = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >; T_sds = Eigen::Array<double, -1, 1>&; stan::require_eigen_t<T_desired>* <anonymous> = 0; stan::require_all_eigen_vector_t<T_CPCs, T_sds>* <anonymous> = 0; stan::require_all_vt_same<T_Sigma, T_CPCs, T_sds>* <anonymous> = 0]'
51 | factor_U(U, CPCs);
| ~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
45 | bool successful = factor_cov_matrix(y, x.array(), sds);
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix<double, -1, -1>; stan::require_not_std_vector_t<Ret>* <anonymous> = 0; T = double]'
480 | this->write(stan::math::corr_matrix_free(x));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer<T>::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector<Eigen::Matrix<double, -1, -1> >; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = double]'
492 | this->write_free_corr_matrix(ret_i);
stanExports_stanmarg.h:19940:0: required from 'void model_stanmarg_namespace::model_stanmarg::transform_inits_impl(const stan::io::var_context&, VecVar&, std::ostream*) const [with VecVar = std::vector<double>; stan::require_vector_t<T_y>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
19940 | out__.write_free_corr_matrix(Psi_r_mat_1);
stanExports_stanmarg.h:22508:0: required from here
22508 | transform_inits_impl(context, vars, pstream__);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from 'static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; int StorageOrder = 1; bool BlasCompatible = true; typename Dest::Scalar = double]'
207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: required from 'struct Eigen::internal::blas_traits<Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
506 | >::type DirectLinearAccessType;
| ^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:422:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, -1>; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, -1>]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, -1>; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, -1>]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Lhs = Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Lhs = Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Rhs = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31: required from 'ExpressionType& Eigen::NoAlias<ExpressionType, StorageBase>::operator=(const StorageBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>; ExpressionType = Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]'
43 | call_assignment_no_alias(m_expression, other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:129:19: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'struct Eigen::internal::gemm_pack_rhs<double, long long int, Eigen::internal::const_blas_data_mapper<double, long long int, 1>, 4, 1, false, true>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:233:85: required from 'static void Eigen::internal::triangular_solve_matrix<Scalar, Index, 2, Mode, Conjugate, TriStorageOrder, 0, OtherInnerStride>::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking<Scalar, Scalar>&) [with Scalar = double; Index = long long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]'
233 | gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr, RhsStorageOrder,false,true> pack_rhs_panel;
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from 'static void Eigen::internal::triangular_solver_selector<Lhs, Rhs, Side, Mode, 0, -1>::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int Side = 2; int Mode = 2]'
100 | triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
101 | (Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor, Rhs::InnerStrideAtCompileTime>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking);
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from 'void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase<OtherDerived>&) const [with int Side = 2; OtherDerived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; _MatrixType = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; unsigned int _Mode = 2]'
181 | internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::type,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
182 | Side, Mode>::run(derived().nestedExpression(), otherCopy);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from 'static Eigen::Index Eigen::internal::llt_inplace<Scalar, 1>::blocked(MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; Scalar = double; Eigen::Index = long long int]'
364 | if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from 'static bool Eigen::internal::LLT_Traits<MatrixType, 1>::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>]'
408 | { return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2504 | typedef typename unpacket_traits<Packet>::half HalfPacket;
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2505 | typedef typename unpacket_traits<typename unpacket_traits<Packet>::half>::half QuarterPacket;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2508 | HalfPacketSize = unpacket_traits<HalfPacket>::size,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2509 | QuarterPacketSize = unpacket_traits<QuarterPacket>::size};
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, -1>, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, -1>, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, -1>, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, -1>, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, -1>, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, -1>, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_left_ldlt.hpp:37:24: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, -1, EigMat::ColsAtCompileTime> stan::math::mdivide_left_ldlt(LDLT_factor<T>&, const EigMat&) [with T = Eigen::Matrix<double, -1, -1>; EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0; stan::require_any_not_t<std::is_arithmetic<typename stan::value_type<T, void>::type>, stan::is_fvar<typename stan::value_type<T_actual, void>::type, void> >* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
37 | return A.ldlt().solve(
| ~~~~~~~~~~~~~~^
38 | Eigen::Matrix<return_type_t<T, EigMat>, EigMat::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
39 | EigMat::ColsAtCompileTime>(b));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<double, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:18267:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18267 | stan::math::wishart_lpdf<false>(
18268 | stan::math::multiply(
18269 | (stan::model::rvalue(N, "N", stan::model::index_uni(mm)) -
18270 | 1),
18271 | stan::model::rvalue(Sstar, "Sstar",
18272 | stan::model::index_uni(mm))),
18273 | (stan::model::rvalue(N, "N", stan::model::index_uni(mm)) -
18274 | 1),
18275 | stan::model::rvalue(Sigma, "Sigma",
18276 | stan::model::index_uni(mm))), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:167:5: required from 'struct boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:125:16: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
125 | struct IncrementableIteratorConcept : CopyConstructible<Iterator>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
147 | struct SinglePassIteratorConcept
| ^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
In file included from D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:31:
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:208:5: required from 'struct boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_<void (*)(boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>)>'
72 | struct requirement_<void(*)(Model)>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_concepts.hpp:114:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]'
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_concepts.hpp:114:7: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
147 | struct SinglePassIteratorConcept
| ^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::Convertible<X, Y>::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
208 | BOOST_CONCEPT_USAGE(Convertible) {
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:136:13: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
147 | struct SinglePassIteratorConcept
| ^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:233:5: required from 'struct boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
147 | struct SinglePassIteratorConcept
| ^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:208:5: required from 'struct boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_<void (*)(boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>)>'
72 | struct requirement_<void(*)(Model)>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:152:13: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]'
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:152:13: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_<void (*)(boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >)>'
72 | struct requirement_<void(*)(Model)>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::Convertible<X, Y>::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
208 | BOOST_CONCEPT_USAGE(Convertible) {
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:158:13: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_<void (*)(boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >)>'
72 | struct requirement_<void(*)(Model)>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:278:9: required from 'struct boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_<void (*)(boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >)>'
72 | struct requirement_<void(*)(Model)>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::range_detail::SinglePassIteratorConcept<Iterator>::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept)
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:284:9: required from 'struct boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_<void (*)(boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >)>'
72 | struct requirement_<void(*)(Model)>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]'
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/algorithm/equal.hpp:174:13: required from 'bool boost::range::equal(const SinglePassRange1&, const SinglePassRange2&) [with SinglePassRange1 = boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; SinglePassRange2 = boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/iterator_range_core.hpp:644:32: required from 'bool boost::operator==(const iterator_range<IteratorT>&, const iterator_range<Iterator2T>&) [with Iterator1T = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >; Iterator2T = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]'
644 | return boost::equal( l, r );
| ~~~~~~~~~~~~^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/find_iterator.hpp:359:0: required from 'bool boost::algorithm::split_iterator<IteratorT>::equal(const boost::algorithm::split_iterator<IteratorT>&) const [with IteratorT = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]'
359 | m_Match==Other.m_Match &&
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:649:26: required from 'static bool boost::iterators::iterator_core_access::equal(const Facade1&, const Facade2&, mpl_::true_) [with Facade1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; Facade2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; mpl_::true_ = mpl_::bool_<true>]'
649 | return f1.equal(f2);
| ~~~~~~~~^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:981:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator==(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; V1 = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; TC1 = forward_traversal_tag; Reference1 = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >&; Difference1 = long long int; Derived2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; V2 = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; TC2 = forward_traversal_tag; Reference2 = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >&; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_adaptor.hpp:305:29: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: warning: 'this' pointer is null [-Wnonnull]
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::SinglePassRangeConcept<T>::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept)
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]'
856 | call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::TriangularShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
145 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
33 | .template triangularView<Eigen::Lower>();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]'
856 | call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::TriangularShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
145 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
33 | .template triangularView<Eigen::Lower>();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]'
462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]'
856 | call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::TriangularShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
145 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
33 | .template triangularView<Eigen::Lower>();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >; Functor = assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >]'
836 | call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:337:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h: In instantiation of 'static void Eigen::internal::selfadjoint_matrix_vector_product<Scalar, Index, StorageOrder, UpLo, ConjugateLhs, ConjugateRhs, Version>::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from 'static void Eigen::internal::selfadjoint_product_impl<Lhs, LhsMode, false, Rhs, 0, true>::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Scalar = double]'
227 | internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
229 | (
| ^
230 | lhs.rows(), // size
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
232 | actualRhsPtr, // rhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
233 | actualDestPtr, // result info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
234 | actualAlpha // scale factor
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
235 | );
| ~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::SelfAdjointShape, Eigen::DenseShape, ProductTag>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]'
805 | selfadjoint_product_impl<typename Lhs::MatrixType,Lhs::Mode,false,Rhs,0,Rhs::IsVectorAtCompileTime>::run(dst, lhs.nestedExpression(), rhs, alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]'
361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
| ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]'
349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
370 | * (conj(h) * matA.col(i).tail(remainingSize)));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
62 | conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> pcj0;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
63 | conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
361 | A21.noalias() -= A20 * temp.head(k);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
361 | A21.noalias() -= A20 * temp.head(k);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_rhs<Scalar, Index, DataMapper, nr, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::blas_data_mapper<double, long long int, 0, 0, 1>; int nr = 4; bool Conjugate = false; bool PanelMode = true]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:155:19: required from 'static void Eigen::internal::triangular_solve_matrix<Scalar, Index, 1, Mode, Conjugate, TriStorageOrder, 0, OtherInnerStride>::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking<Scalar, Scalar>&) [with Scalar = double; Index = long long int; int Mode = 1; bool Conjugate = false; int TriStorageOrder = 0; int OtherInnerStride = 1]'
155 | pack_rhs(blockB+actual_kc*j2, other.getSubMapper(startBlock,j2), actualPanelWidth, actual_cols, actual_kc, blockBOffset);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from 'static void Eigen::internal::triangular_solver_selector<Lhs, Rhs, Side, Mode, 0, -1>::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Matrix<double, -1, -1>; int Side = 1; int Mode = 1]'
100 | triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
101 | (Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor, Rhs::InnerStrideAtCompileTime>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking);
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from 'void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase<OtherDerived>&) const [with int Side = 1; OtherDerived = Eigen::Matrix<double, -1, -1>; _MatrixType = const Eigen::Matrix<double, -1, -1>; unsigned int _Mode = 1]'
181 | internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::type,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
182 | Side, Mode>::run(derived().nestedExpression(), otherCopy);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:522:37: required from 'void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Matrix<double, -1, -1>; _MatrixType = const Eigen::Matrix<double, -1, -1>; unsigned int _Mode = 1]'
522 | { return solveInPlace<OnTheLeft>(other); }
| ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:520:25: required from 'void Eigen::LLT<MatrixType, UpLo>::solveInPlace(const Eigen::MatrixBase<OtherDerived>&) const [with Derived = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
520 | matrixL().solveInPlace(bAndX);
| ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:56:0: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4445:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2459 | PacketBlock<Packet,(PacketSize%4)==0?4:PacketSize> kernel;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:22: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:37: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; int ProductTag = 6; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1632:27: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; int ProductTag = 6; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1632:27: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:22: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:37: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; int ProductTag = 6; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1632:27: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; int ProductTag = 6; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1632:27: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, member_sum<double, double>, 0>; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0> >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>; typename Eigen::internal::traits<T>::Scalar = double]'
466 | return maxCoeff<PropagateFast>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533:57: required from 'void Eigen::PartialPivLU<MatrixType>::compute() [with _MatrixType = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
533 | m_l1_norm = m_lu.cwiseAbs().colwise().sum().maxCoeff();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:133:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 2, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 2, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 2, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 2, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 2, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 2, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 2, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 2, true> >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:217:20: required from 'PacketType Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; int Direction = 0; Eigen::Index = long long int]'
217 | PanelEvaluator panel_eval(panel);
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0> >; Scalar = double]'
251 | PacketScalar packet_res0 = eval.template packet<alignment,PacketScalar>(alignedStart);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::internal::member_sum<double, double>, 0>; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1, 1, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1, 1, -1, -1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Scalar = double]'
347 | return derived() = Constant(rows(), cols(), val);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase<Derived>::setZero() [with Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
548 | return setConstant(Scalar(0));
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:444:18: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::Matrix<double, 1, -1>; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix<double, 1, -1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::Matrix<double, 1, -1> >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::Matrix<double, 1, -1>; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::Matrix<double, 1, -1>; typename Eigen::internal::traits<T>::Scalar = double]'
448 | return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::Matrix<double, 1, -1>; typename Eigen::internal::traits<T>::Scalar = double]'
466 | return maxCoeff<PropagateFast>();
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:511:85: required from 'void Eigen::ColPivHouseholderQR<MatrixType>::computeInPlace() [with _MatrixType = Eigen::Matrix<double, -1, -1>]'
511 | RealScalar threshold_helper = numext::abs2<RealScalar>(m_colNormsUpdated.maxCoeff() * NumTraits<RealScalar>::epsilon()) / RealScalar(rows);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:477:3: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>'
564 | CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, Packet, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::blas_data_mapper<double, long long int, 0, 0, 1>; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = true]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:319:27: required from 'static void Eigen::internal::triangular_solve_matrix<Scalar, Index, 2, Mode, Conjugate, TriStorageOrder, 0, OtherInnerStride>::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking<Scalar, Scalar>&) [with Scalar = double; Index = long long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]'
319 | pack_lhs_panel(blockA, lhs.getSubMapper(i2,absolute_j2),
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
320 | actualPanelWidth, actual_mc,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
321 | actual_kc, j2);
| ~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from 'static void Eigen::internal::triangular_solver_selector<Lhs, Rhs, Side, Mode, 0, -1>::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int Side = 2; int Mode = 2]'
100 | triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
101 | (Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor, Rhs::InnerStrideAtCompileTime>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking);
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from 'void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase<OtherDerived>&) const [with int Side = 2; OtherDerived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; _MatrixType = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; unsigned int _Mode = 2]'
181 | internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::type,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
182 | Side, Mode>::run(derived().nestedExpression(), otherCopy);
| ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from 'static Eigen::Index Eigen::internal::llt_inplace<Scalar, 1>::blocked(MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; Scalar = double; Eigen::Index = long long int]'
364 | if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from 'static bool Eigen::internal::LLT_Traits<MatrixType, 1>::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>]'
408 | { return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2100 | typedef typename unpacket_traits<typename unpacket_traits<Packet>::half>::half QuarterPacket;
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2102 | HalfPacketSize = unpacket_traits<HalfPacket>::size,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
2103 | QuarterPacketSize = unpacket_traits<QuarterPacket>::size,
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:29:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>'
113 | LhsNested m_lhs;
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:29:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, 1>, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, 1>, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, 1>, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, 1>, 2, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, 1>, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Matrix<double, -1, 1>, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, 1>, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, 1>, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, 1>, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, 1>, 2, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, 1>, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Matrix<double, -1, 1>, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:610:38: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]'
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:167:5: required from 'struct boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:125:16: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
125 | struct IncrementableIteratorConcept : CopyConstructible<Iterator>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
147 | struct SinglePassIteratorConcept
| ^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull]
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::CopyConstructible<TT>::~CopyConstructible() [with TT = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:167:5: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
167 | BOOST_CONCEPT_USAGE(CopyConstructible) {
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >]'
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:208:5: required from 'struct boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull]
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::Convertible<X, Y>::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
208 | BOOST_CONCEPT_USAGE(Convertible) {
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]'
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:136:13: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
147 | struct SinglePassIteratorConcept
| ^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull]
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::range_detail::IncrementableIteratorConcept<Iterator>::~IncrementableIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:136:13: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
136 | BOOST_CONCEPT_USAGE(IncrementableIteratorConcept)
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]'
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:233:5: required from 'struct boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
147 | struct SinglePassIteratorConcept
| ^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull]
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::EqualityComparable<TT>::~EqualityComparable() [with TT = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:233:5: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
233 | BOOST_CONCEPT_USAGE(EqualityComparable) {
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >]'
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:208:5: required from 'struct boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull]
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::Convertible<X, Y>::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
208 | BOOST_CONCEPT_USAGE(Convertible) {
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]'
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:158:13: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull]
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::range_detail::SinglePassIteratorConcept<Iterator>::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept)
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements<Model>::~usage_requirements() [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]':
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >]'
50 | static void failed() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:284:9: required from 'struct boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >'
92 | &::boost::concepts::requirement_<ModelFnPtr>::failed> \
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]'
32 | inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::constraints>* = 0);
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >::value'
44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) );
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >'
45 | typedef boost::integral_constant<bool, value> type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]'
966 | return_prefix iterator_core_access::base_op( \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
967 | *static_cast<Derived1 const*>(&lhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
968 | , *static_cast<Derived2 const*>(&rhs) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
970 | ); \
| ~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:1673:21: required from 'void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]'
1673 | for (; __first != __last; ++__first)
| ~~~~~~~~^~~~~~~~~
D:/rtools45/x86_64-w64-mingw32.static.posix/lib/gcc/x86_64-w64-mingw32.static.posix/14.2.0/include/c++/bits/stl_vector.h:711:23: required from 'std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]'
711 | _M_range_initialize(__first, __last,
| ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~
712 | std::__iterator_category(__first));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]'
186 | SequenceSequenceT Tmp(itBegin, itEnd);
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/algorithm/string/split.hpp:158:0: required from 'SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]'
158 | return ::boost::algorithm::iter_split(
159 | Result,
160 | Input,
161 | ::boost::algorithm::token_finder( Pred, eCompress ) );
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here
19 | boost::split(parts, variable, boost::is_any_of(":"));
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull]
20 | ~usage_requirements() { ((Model*)0)->~Model(); }
| ~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::SinglePassRangeConcept<T>::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]'
37 | ~model()
| ^
D:/RCompile/CRANpkg/lib/4.6/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro 'BOOST_CONCEPT_USAGE'
284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept)
| ^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]'
856 | call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::TriangularShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
145 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
33 | .template triangularView<Eigen::Lower>();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:166:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/Memory.h: In instantiation of 'Index Eigen::internal::first_default_aligned(const Scalar*, Index) [with Scalar = double; Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:89:68: required from 'static void Eigen::internal::selfadjoint_matrix_vector_product<Scalar, Index, StorageOrder, UpLo, ConjugateLhs, ConjugateRhs, Version>::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]'
89 | Index alignedStart = (starti) + internal::first_default_aligned(&res[starti], endi-starti);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from 'static void Eigen::internal::selfadjoint_product_impl<Lhs, LhsMode, false, Rhs, 0, true>::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Scalar = double]'
227 | internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
229 | (
| ^
230 | lhs.rows(), // size
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
232 | actualRhsPtr, // rhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
233 | actualDestPtr, // result info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
234 | actualAlpha // scale factor
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
235 | );
| ~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::SelfAdjointShape, Eigen::DenseShape, ProductTag>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]'
805 | selfadjoint_product_impl<typename Lhs::MatrixType,Lhs::Mode,false,Rhs,0,Rhs::IsVectorAtCompileTime>::run(dst, lhs.nestedExpression(), rhs, alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]'
361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
| ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]'
349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
370 | * (conj(h) * matA.col(i).tail(remainingSize)));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
449 | tridiagonalization_inplace(mat, hCoeffs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/Memory.h:500:60: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
500 | return first_aligned<unpacket_traits<DefaultPacketType>::alignment>(array, size);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:167:27: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:170:53: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:170:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:129:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:132:29: required from 'void Eigen::MatrixBase<Derived>::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Scalar = double]'
132 | bottom.noalias() -= tau * essential * tmp;
| ~~~~^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, 5>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:132:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here
22 | vector_d eigenprojections = eigenvectors.transpose() * g;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
332 | Base::template _init1<T>(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
850 | typename plain_matrix_type<Src>::type tmp(src);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>]'
836 | call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]'
779 | internal::call_assignment(this->derived(), other.derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]'
225 | return Base::_set(other);
| ~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here
26 | g = eigenvectors * eigenprojections;
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:114:15: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:114:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpositions<-1, -1, int>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpositions<-1, -1, int>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S);
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:610:38: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S);
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:114:15: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >'
1043 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>'
564 | CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from 'class Eigen::internal::visitor_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >'
79 | CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>'
564 | CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from 'class Eigen::internal::visitor_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >'
79 | CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from 'void Eigen::DenseBase<Derived>::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor<Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_score_coeff_op<double>, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >]'
123 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, 1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, 1, -1> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Matrix<double, 1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<double, 1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Matrix<double, 1, -1>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Matrix<double, 1, -1> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
98 | return numext::real((*this).cwiseAbs2().sum());
| ~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:110:23: required from 'typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::norm() const [with Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]'
110 | return numext::sqrt(squaredNorm());
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:507:52: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:67: required from 'Derived& Eigen::DenseBase<Derived>::operator/=(const Scalar&) [with Derived = Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>; Scalar = double]'
41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:599:18: required from 'void Eigen::LDLT<MatrixType, UpLo>::_solve_impl_transposed(const RhsType&, DstType&) const [with bool Conjugate = true; RhsType = Eigen::Matrix<double, -1, 1>; DstType = Eigen::Matrix<double, -1, 1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
599 | dst.row(i) /= vecD(i);
| ~~~~~~~~~~~^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:569:31: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>; Derived = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_rhs<Scalar, Index, DataMapper, nr, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::const_blas_data_mapper<double, long long int, 0>; int nr = 4; bool Conjugate = false; bool PanelMode = true]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:346:25: required from 'static void Eigen::internal::product_triangular_matrix_matrix<Scalar, Index, Mode, false, LhsStorageOrder, ConjugateLhs, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, Version>::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking<Scalar, Scalar>&) [with Scalar = double; Index = long long int; int Mode = 1; int LhsStorageOrder = 1; bool ConjugateLhs = false; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]'
346 | pack_rhs_panel(blockB+j2*actual_kc,
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
347 | rhs.getSubMapper(actual_k2+panelOffset, actual_j2),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
348 | panelLength, actualPanelWidth,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
349 | actual_kc, panelOffset);
| ~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]'
438 | internal::product_triangular_matrix_matrix<Scalar, Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
439 | Mode, LhsIsTriangular,
| ~~~~~~~~~~~~~~~~~~~~~~
440 | (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
441 | (internal::traits<ActualRhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
442 | (internal::traits<Dest >::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
443 | ::run(
| ~~~~~^
444 | stripedRows, stripedCols, stripedDepth, // sizes
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
448 | actualAlpha, blocking
| ~~~~~~~~~~~~~~~~~~~~~
449 | );
| ~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::TriangularShape, ProductTag>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>; int ProductTag = 8; Scalar = double]'
783 | triangular_product_impl<Rhs::Mode,false,Lhs,Lhs::RowsAtCompileTime==1, typename Rhs::MatrixType, false>::run(dst, lhs, rhs.nestedExpression(), alpha);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>; Scalar = double]'
361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
| ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>]'
349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]'
856 | call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::TriangularShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
145 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
33 | .template triangularView<Eigen::Lower>();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
2459 | PacketBlock<Packet,(PacketSize%4)==0?4:PacketSize> kernel;
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:99:96: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:101:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:102:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:103:22: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
361 | A21.noalias() -= A20 * temp.head(k);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from 'static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]'
361 | A21.noalias() -= A20 * temp.head(k);
| ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
526 | m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]'
120 | compute(matrix.derived());
| ~~~~~~~^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
683 | return LDLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from 'void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]'
45 | Eigen::LDLT<Eigen::MatrixXd> cholesky = value_of_rec(y_ref).ldlt();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here
21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric",
22 | inv_metric);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true>; Derived = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; SrcXprType = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; Functor = swap_assign_op<double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; SrcXprType = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; Functor = Eigen::internal::swap_assign_op<double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; Src = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; Func = swap_assign_op<double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; Src = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; Func = swap_assign_op<double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:424:22: required from 'void Eigen::DenseBase<Derived>::swap(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; Derived = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>]'
424 | call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:483:24: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Lhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:464:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::subTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Lhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >]'
464 | scaleAndAddTo(dst, lhs, rhs, Scalar(-1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Lhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:464:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::subTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Lhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >]'
464 | scaleAndAddTo(dst, lhs, rhs, Scalar(-1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::PermutationMatrix<-1, -1, int>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::PermutationMatrix<-1, -1, int>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::PermutationMatrix<-1, -1, int>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::PermutationMatrix<-1, -1, int>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::PermutationMatrix<-1, -1, int>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::PermutationMatrix<-1, -1, int>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:234:28: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~~~
40 | .solve(Eigen::Matrix<T_return, Eigen::Dynamic, Eigen::Dynamic>(b)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
41 | .transpose())
| ~~~~~~~~~~~~~
42 | .transpose();
| ~~~~~~~~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from 'Derived& Eigen::MatrixBase<Derived>::operator=(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>; Derived = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
66 | internal::call_assignment(derived(), other.derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_vector.hpp:22:11: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::to_vector(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
22 | res_map = matrix;
| ~~~~~~~~^~~~~~~~
stanExports_stanmarg.h:15802:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15802 | stan::math::to_vector(
15803 | stan::math::multiply(
15804 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15805 | stan::model::index_uni(g)),
15806 | stan::model::rvalue(Alpha, "Alpha",
15807 | stan::model::index_uni(g),
15808 | stan::model::index_min_max(1, m),
15809 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >; Functor = div_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >; Functor = Eigen::internal::div_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >; Func = div_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >; Func = div_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from 'Derived& Eigen::DenseBase<Derived>::operator/=(const Scalar&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; Scalar = double]'
41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:333:21: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]'
457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]'
462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>; Scalar = double]'
347 | return derived() = Constant(rows(), cols(), val);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase<Derived>::setZero() [with Derived = Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>]'
548 | return setConstant(Scalar(0));
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:42: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]'
856 | call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::TriangularShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
145 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
33 | .template triangularView<Eigen::Lower>();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:90: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:57: required from 'void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; VectorsType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; CoeffsType = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>]'
63 | triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint()
| ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:64:57: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:73:50: required from 'void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; VectorsType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; CoeffsType = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>]'
73 | triFactor.row(i).tail(nbVecs-j-1) += z * triFactor.row(j).tail(nbVecs-j-1);
| ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Lhs = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Lhs = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
48 | arena_B.adj() += arena_A_val.transpose() * res_adj;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from 'static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; typename Dest::Scalar = double]'
366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from 'static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; int StorageOrder = 1; bool BlasCompatible = true; typename Dest::Scalar = double]'
207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: required from 'static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; int StorageOrder = 0; bool BlasCompatible = false; typename Dest::Scalar = double]'
207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:52: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from 'static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; typename Dest::Scalar = double]'
366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from 'static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; int StorageOrder = 0; bool BlasCompatible = false; typename Dest::Scalar = double]'
207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: required from 'static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Rhs = Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; int StorageOrder = 1; bool BlasCompatible = false; typename Dest::Scalar = double]'
207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:610:38: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 2>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 2> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 2> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 2, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 2, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpositions<-1, -1, int>, Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 2>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Matrix<double, 1, -1>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false> >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false>; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false>; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from 'ResultType Eigen::internal::member_sum<ResultType, Scalar>::operator()(const XprType&) const [with XprType = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, false>; ResultType = double; Scalar = double]'
97 | { return mat.MEMBER(); } \
| ~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from 'const Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::Scalar Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; int Direction = 0; Scalar = double; Eigen::Index = long long int]'
183 | return m_functor(m_arg.template subVector<DirectionType(Direction)>(index));
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/Memory.h:639:76: required from 'void Eigen::internal::outer_product_selector_run(Dst&, const Lhs&, const Rhs&, const Func&, const true_type&) [with Dst = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>; Lhs = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>; Rhs = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>; Func = generic_product_impl<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::DenseShape, Eigen::DenseShape, 5>::sub]'
639 | bool MapExternalBuffer = nested_eval<Xpr,NbEvaluations>::Evaluate && Xpr::MaxSizeAtCompileTime==Dynamic
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:329:41: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 5>::subTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>; Lhs = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>; Rhs = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>]'
329 | internal::outer_product_selector_run(dst, lhs, rhs, sub(), is_row_major<Dst>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::sub_assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>; Lhs = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>; Rhs = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>]'
178 | generic_product_impl<Lhs, Rhs>::subTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>; Src = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:293:48: required from 'void Eigen::internal::outer_product_selector_run(Dst&, const Lhs&, const Rhs&, const Func&, const true_type&) [with Dst = Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>; Lhs = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>; Rhs = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>; Func = generic_product_impl<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::DenseShape, Eigen::DenseShape, 5>::sub]'
293 | func(dst.row(i), lhsEval.coeff(i,Index(0)) * actual_rhs);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:329:41: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:17369:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17369 | stan::math::tcrossprod(
17370 | stan::math::to_matrix(
17371 | stan::math::subtract(
17372 | stan::model::rvalue(YXstar_rep, "YXstar_rep",
17373 | stan::model::index_uni(ii)),
17374 | stan::model::rvalue(mean_d_rep, "mean_d_rep",
17375 | stan::model::index_uni(clusidx)))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; typename Dest::Scalar = double]'
457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, -1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; typename Dest::Scalar = double]'
462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, 64>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits<Eigen::Matrix<double, 8, 8, 0, 8, 8> >'
22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 8, 8, 0, 8, 8> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix<double, 8, 8, 0, 8, 8>'
178 | class Matrix
| ^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:150:68: required from 'static void Eigen::internal::product_triangular_matrix_matrix<Scalar, Index, Mode, true, LhsStorageOrder, ConjugateLhs, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, Version>::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking<Scalar, Scalar>&) [with Scalar = double; Index = long long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]'
150 | Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer(a);
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]'
438 | internal::product_triangular_matrix_matrix<Scalar, Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
439 | Mode, LhsIsTriangular,
| ~~~~~~~~~~~~~~~~~~~~~~
440 | (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
441 | (internal::traits<ActualRhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
442 | (internal::traits<Dest >::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
443 | ::run(
| ~~~~~^
444 | stripedRows, stripedCols, stripedDepth, // sizes
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
448 | actualAlpha, blocking
| ~~~~~~~~~~~~~~~~~~~~~
449 | );
| ~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 8, 8, 0, 8, 8> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 8, 8, 0, 8, 8> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 8, 8, 0, 8, 8> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet<double, 8>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0> >'
179 | typedef typename internal::find_best_packet<Scalar,SizeAtCompileTime>::type PacketScalar;
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: required from 'static void Eigen::internal::product_triangular_matrix_matrix<Scalar, Index, Mode, true, LhsStorageOrder, ConjugateLhs, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, Version>::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking<Scalar, Scalar>&) [with Scalar = double; Index = long long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]'
153 | triangularBuffer.diagonal().setZero();
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]'
438 | internal::product_triangular_matrix_matrix<Scalar, Index,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
439 | Mode, LhsIsTriangular,
| ~~~~~~~~~~~~~~~~~~~~~~
440 | (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
441 | (internal::traits<ActualRhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
442 | (internal::traits<Dest >::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
443 | ::run(
| ~~~~~^
444 | stripedRows, stripedCols, stripedDepth, // sizes
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
448 | actualAlpha, blocking
| ~~~~~~~~~~~~~~~~~~~~~
449 | );
| ~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
190 | bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::half>::value>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::unpacket_traits<__vector(2) double>::half' {aka '__m128d'} [-Wignored-attributes]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
208 | typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>]'
148 | generic_product_impl<Lhs, Rhs>::evalTo(dst, src.lhs(), src.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31: required from 'ExpressionType& Eigen::NoAlias<ExpressionType, StorageBase>::operator=(const StorageBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>; ExpressionType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]'
43 | call_assignment_no_alias(m_expression, other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:167:19: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Matrix<double, -1, -1>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:769:69: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
38 | arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
57 | arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
68 | arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>'
370 | typedef typename nested_eval<Rhs,1>::type RhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Scalar = double]'
478 | return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:43: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from 'static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >; typename Dest::Scalar = double]'
379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:43: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from 'static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >; typename Dest::Scalar = double]'
379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:52: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from 'static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >; typename Dest::Scalar = double]'
366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from 'static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Dest = Eigen::Transpose<Eigen::Matrix<double, 1, -1> >; typename Dest::Scalar = double]'
379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from 'Derived& Eigen::MatrixBase<Derived>::operator=(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>; Derived = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
66 | internal::call_assignment(derived(), other.derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_vector.hpp:22:11: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::to_vector(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
22 | res_map = matrix;
| ~~~~~~~~^~~~~~~~
stanExports_stanmarg.h:15802:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15802 | stan::math::to_vector(
15803 | stan::math::multiply(
15804 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15805 | stan::model::index_uni(g)),
15806 | stan::model::rvalue(Alpha, "Alpha",
15807 | stan::model::index_uni(g),
15808 | stan::model::index_min_max(1, m),
15809 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3272 | stan::model::assign(Sigma_yz_zi,
3273 | stan::math::multiply(Sigma_yz, Sigma_zz_inv),
3274 | "assigning variable Sigma_yz_zi");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3272 | stan::model::assign(Sigma_yz_zi,
3273 | stan::math::multiply(Sigma_yz, Sigma_zz_inv),
3274 | "assigning variable Sigma_yz_zi");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:125:66: required from 'static void Eigen::internal::triangular_solve_vector<LhsScalar, RhsScalar, Index, 1, Mode, Conjugate, 0>::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long long int; int Mode = 5; bool Conjugate = false]'
125 | Map<Matrix<RhsScalar,Dynamic,1> >(rhs+s,r) -= rhs[i] * cjLhs.col(i).segment(s,r);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >'
94 | template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:39:18: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:57: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:72: required from 'static void Eigen::internal::triangular_solve_vector<LhsScalar, RhsScalar, Index, 1, Mode, Conjugate, 1>::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long long int; int Mode = 6; bool Conjugate = false]'
78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map<const Matrix<RhsScalar,Dynamic,1> >(rhs+s,k))).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 4, 4, 1, 4, 4> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 4, 4, 1, 4, 4> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 4, 1, 4, 4> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1> >; Functor = Eigen::internal::assign_op<double, double>; int Version = 1; Eigen::Index = long long int]'
654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]'
856 | call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::TriangularShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
145 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
33 | .template triangularView<Eigen::Lower>();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]'
856 | call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::TriangularShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]'
145 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
31 | arena_L.adj() += ((res.adj().transpose() + res.adj())
32 | * arena_L_val.template triangularView<Eigen::Lower>())
33 | .template triangularView<Eigen::Lower>();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1> >; Functor = Eigen::internal::assign_op<double, double>; int Version = 1; Eigen::Index = long long int]'
654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
29 | return M_ref * M_ref.transpose();
| ~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:18036:0: required from here
18036 | stan::math::divide(stan::math::crossprod(YXsmat),
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from 'static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Dest = Eigen::Matrix<double, -1, 1>; typename Dest::Scalar = double]'
366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
68 | arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, -1>; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Matrix<double, -1, -1>; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Matrix<double, -1, -1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15744:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15744 | stan::math::quad_form_sym(
15745 | stan::model::rvalue(Psi_r, "Psi_r", stan::model::index_uni(g)),
15746 | stan::model::rvalue(Psi_sd, "Psi_sd", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3272 | stan::model::assign(Sigma_yz_zi,
3273 | stan::math::multiply(Sigma_yz, Sigma_zz_inv),
3274 | "assigning variable Sigma_yz_zi");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >; Functor = div_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >; Functor = Eigen::internal::div_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >; Func = div_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >; Func = div_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from 'Derived& Eigen::DenseBase<Derived>::operator/=(const Scalar&) [with Derived = Eigen::Block<Eigen::Matrix<double, -1, 1>, 1, 1, false>; Scalar = double]'
41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:599:18: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 0, 8, 8> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 0, 8, 8> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 0, 8, 8> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 0, 8, 8> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, 8, 8, 0, 8, 8>; Scalar = double]'
347 | return derived() = Constant(rows(), cols(), val);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase<Derived>::setZero() [with Derived = Eigen::Matrix<double, 8, 8, 0, 8, 8>]'
548 | return setConstant(Scalar(0));
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 1, 0, 8, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 1, 0, 8, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 1, 0, 8, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 1, 0, 8, 1> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>; Scalar = double]'
347 | return derived() = Constant(rows(), cols(), val);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase<Derived>::setZero() [with Derived = Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>]'
548 | return setConstant(Scalar(0));
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:42: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Functor = add_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Functor = Eigen::internal::add_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
177 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Householder/Householder.h:168:9: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:74: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, std::allocator<Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value<double>; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = stan::math::var_value<double>; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
12985 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
12986 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
12987 | Psi_r_mat_1_3dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]'
462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, std::allocator<Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value<double>; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = stan::math::var_value<double>; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
12985 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
12986 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
12987 | Psi_r_mat_1_3dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
38 | arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
38 | arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
57 | arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
68 | arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
68 | arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; SrcXprType = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> >; Functor = div_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> >; Functor = Eigen::internal::div_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> >; Func = div_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> >; Func = div_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from 'Derived& Eigen::DenseBase<Derived>::operator/=(const Scalar&) [with Derived = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; Scalar = double]'
41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:599:18: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S);
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>]'
177 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from 'Derived& Eigen::MatrixBase<Derived>::operator=(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>; Derived = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]'
66 | internal::call_assignment(derived(), other.derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_vector.hpp:22:11: required from 'Eigen::Matrix<typename stan::value_type<T>::type, -1, 1> stan::math::to_vector(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
22 | res_map = matrix;
| ~~~~~~~~^~~~~~~~
stanExports_stanmarg.h:15802:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15802 | stan::math::to_vector(
15803 | stan::math::multiply(
15804 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15805 | stan::model::index_uni(g)),
15806 | stan::model::rvalue(Alpha, "Alpha",
15807 | stan::model::index_uni(g),
15808 | stan::model::index_min_max(1, m),
15809 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:4181:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4181 | stan::model::assign(T2p11,
4182 | stan::math::subtract(Sig11,
4183 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4184 | stan::math::transpose(Sig12))), "assigning variable T2p11");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:4181:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4181 | stan::model::assign(T2p11,
4182 | stan::math::subtract(Sig11,
4183 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4184 | stan::math::transpose(Sig12))), "assigning variable T2p11");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true>; Derived = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
1043 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4, 1, 4, 4> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4, 1, 4, 4> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4, 1, 4, 4> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4, 1, 4, 4> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, 4, 4, 1, 4, 4>; Scalar = double]'
347 | return derived() = Constant(rows(), cols(), val);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase<Derived>::setZero() [with Derived = Eigen::Matrix<double, 4, 4, 1, 4, 4>]'
548 | return setConstant(Scalar(0));
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:301:29: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
48 | arena_B.adj() += arena_A_val.transpose() * res_adj;
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:37: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from 'static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >; typename Dest::Scalar = double]'
379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Matrix<double, -1, -1>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Functor = sub_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Derived = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:305:153: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::llt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
542 | return LLT<PlainObject>(derived());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:24:47: required from 'Eigen::MatrixXd stan::math::wishart_rng(double, const Eigen::MatrixXd&, RNG&) [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::MatrixXd = Eigen::Matrix<double, -1, -1>]'
24 | Eigen::LLT<Eigen::MatrixXd> llt_of_S = S.llt();
| ~~~~~^~
stanExports_stanmarg.h:17122:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17122 | stan::math::wishart_rng(
17123 | (stan::model::rvalue(N, "N", stan::model::index_uni(g)) - 1),
17124 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g)),
17125 | base_rng__), "assigning variable Sigma_rep_sat",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, 1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:4192:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4192 | stan::model::assign(ymis,
4193 | stan::math::add(
4194 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx),
4195 | stan::model::index_multi(
4196 | stan::model::rvalue(obsidx, "obsidx",
4197 | stan::model::index_min_max(
4198 | (stan::model::rvalue(Nobs, "Nobs",
4199 | stan::model::index_uni(mm)) + 1), p)))),
4200 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4201 | stan::math::subtract(
4202 | stan::model::rvalue(YXstar, "YXstar",
4203 | stan::model::index_uni(jj),
4204 | stan::model::index_min_max(1,
4205 | stan::model::rvalue(Nobs, "Nobs",
4206 | stan::model::index_uni(mm)))),
4207 | stan::model::rvalue(Mu, "Mu",
4208 | stan::model::index_uni(grpidx),
4209 | stan::model::index_multi(
4210 | stan::model::rvalue(obsidx, "obsidx",
4211 | stan::model::index_min_max(1,
4212 | stan::model::rvalue(Nobs, "Nobs",
4213 | stan::model::index_uni(mm))))))))),
4214 | "assigning variable ymis");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3272 | stan::model::assign(Sigma_yz_zi,
3273 | stan::math::multiply(Sigma_yz, Sigma_zz_inv),
3274 | "assigning variable Sigma_yz_zi");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3272 | stan::model::assign(Sigma_yz_zi,
3273 | stan::math::multiply(Sigma_yz, Sigma_zz_inv),
3274 | "assigning variable Sigma_yz_zi");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 1, 0, 8, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 1, 0, 8, 1>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 1, 0, 8, 1>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 8, 1, 0, 8, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 8, 1, 0, 8, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 8, 1, 0, 8, 1> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
123 | Base::operator=(a);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]'
68 | *this = other;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]'
722 | : val_(x),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]'
366 | var_value(S&& x) : vi_(new vari_type(std::forward<S>(x), false)) {} // NOLINT
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from 'auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]'
27 | arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here
59 | return multiply_lower_tri_self_transpose(L);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::add_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]'
40 | _Hk = Hupd * _Hk * Hupd.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_stanmarg_namespace::model_stanmarg, false>; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]'
246 | Scalar B0fact = _qn.update(yk, sk, true);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from 'int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_stanmarg_namespace::model_stanmarg; bool jacobian = false]'
117 | ret = bfgs.step();
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector<long long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Rcpp::List = Rcpp::Vector<19>]'
517 | = stan::services::optimize::bfgs(model, *init_context_ptr,
518 | random_seed, id, init_radius,
519 | init_alpha,
520 | tol_obj,
521 | tol_rel_obj,
522 | tol_grad,
523 | tol_rel_grad,
524 | tol_param,
525 | num_iterations,
526 | save_iterations,
527 | refresh,
528 | interrupt, logger,
529 | init_writer, sample_writer);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1215 | ret = command(args, model_, holder, names_oi_tidx_,
1216 | fnames_oi_, base_rng);
stanExports_stanmarg.cc:15:0: required from here
15 | .method("call_sampler", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::call_sampler)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix<var_value<double>, -1, -1>; T2 = Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<var_value<double>, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]'
57 | arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
13638 | stan::math::multiply(
13639 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
13640 | stan::model::index_uni(g)),
13641 | stan::model::rvalue(Alpha, "Alpha",
13642 | stan::model::index_uni(g),
13643 | stan::model::index_min_max(1, m),
13644 | stan::model::index_uni(1))))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >; Functor = add_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >; Functor = Eigen::internal::add_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T10__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T11__ = Eigen::Matrix<stan::math::var_value<double>, -1, 1>; T12__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = stan::math::var_value<double>; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T9__, void>::type = stan::math::var_value<double>; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = stan::math::var_value<double>; typename stan::base_type<T10__, void>::type = stan::math::var_value<double>; typename stan::base_type<T11__, void>::type = stan::math::var_value<double>; typename stan::base_type<T12__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
3306 | stan::math::crossprod(
3307 | stan::math::transpose(
3308 | stan::math::to_matrix(
3309 | stan::math::subtract(
3310 | stan::model::rvalue(mean_d, "mean_d",
3311 | stan::model::index_uni(clz)), Mu_full)))),
stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14275 | lp_accum__.add(twolevel_logdens(
14276 | stan::model::rvalue(mean_d, "mean_d",
14277 | stan::model::index_min_max(r3, r4)),
14278 | stan::model::rvalue(cov_d, "cov_d",
14279 | stan::model::index_min_max(r3, r4)),
14280 | stan::model::rvalue(S_PW, "S_PW",
14281 | stan::model::index_uni(grpidx)),
14282 | stan::model::rvalue(YX, "YX",
14283 | stan::model::index_min_max(rr1, rr2)),
14284 | stan::model::rvalue(nclus, "nclus",
14285 | stan::model::index_uni(grpidx),
14286 | stan::model::index_omni()),
14287 | stan::model::rvalue(cluster_size,
14288 | "cluster_size",
14289 | stan::model::index_min_max(r1, r2)),
14290 | stan::model::rvalue(cluster_sizes,
14291 | "cluster_sizes",
14292 | stan::model::index_min_max(r3, r4)),
14293 | stan::model::rvalue(ncluster_sizes,
14294 | "ncluster_sizes",
14295 | stan::model::index_uni(grpidx)),
14296 | stan::model::rvalue(cluster_size_ns,
14297 | "cluster_size_ns",
14298 | stan::model::index_min_max(r3, r4)),
14299 | stan::model::rvalue(Mu, "Mu",
14300 | stan::model::index_uni(grpidx)),
14301 | stan::model::rvalue(Sigma, "Sigma",
14302 | stan::model::index_uni(grpidx)),
14303 | stan::model::rvalue(Mu_c, "Mu_c",
14304 | stan::model::index_uni(grpidx)),
14305 | stan::model::rvalue(Sigma_c, "Sigma_c",
14306 | stan::model::index_uni(grpidx)), ov_idx1,
14307 | ov_idx2, within_idx, between_idx, both_idx,
14308 | p_tilde, N_within, N_between, N_both, pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >; Functor = div_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >; Functor = Eigen::internal::div_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >; Func = div_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, 1, 1, 0, 1, 1> >; Func = div_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from 'Derived& Eigen::DenseBase<Derived>::operator/=(const Scalar&) [with Derived = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1, 1, false>; Scalar = double]'
41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:599:18: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -1>; T1__ = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; T3__ = Eigen::Block<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, -1, -1, false>; stan::require_all_t<stan::is_col_vector<T>, stan::is_vt_not_complex<T0__>, stan::is_eigen_matrix_dynamic<Mat2>, stan::is_vt_not_complex<T1__>, stan::is_col_vector<T4__>, stan::is_vt_not_complex<T2__>, stan::is_eigen_matrix_dynamic<T3__>, stan::is_vt_not_complex<T3__> >* <anonymous> = 0; stan::promote_args_t<typename stan::base_type<T, void>::type, typename stan::base_type<T1__, void>::type, typename stan::base_type<T2__, void>::type, typename stan::base_type<T3__, void>::type> = stan::math::var_value<double>; typename stan::base_type<T>::type = double; typename stan::base_type<T1__, void>::type = double; typename stan::base_type<T2__, void>::type = stan::math::var_value<double>; typename stan::base_type<T3__, void>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4502 | stan::math::multiply(stan::math::subtract(xbar, Mu),
4503 | stan::math::transpose(stan::math::subtract(xbar, Mu))))))
stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14485 | lp_accum__.add(multi_normal_suff(
14486 | stan::model::rvalue(YXbarstar,
14487 | "YXbarstar", stan::model::index_uni(mm),
14488 | stan::model::index_min_max(1,
14489 | stan::model::rvalue(Nobs, "Nobs",
14490 | stan::model::index_uni(mm)))),
14491 | stan::model::rvalue(Sstar, "Sstar",
14492 | stan::model::index_uni(mm),
14493 | stan::model::index_min_max(1,
14494 | stan::model::rvalue(Nobs, "Nobs",
14495 | stan::model::index_uni(mm))),
14496 | stan::model::index_min_max(1,
14497 | stan::model::rvalue(Nobs, "Nobs",
14498 | stan::model::index_uni(mm)))),
14499 | stan::model::rvalue(Mu, "Mu",
14500 | stan::model::index_uni(grpidx),
14501 | stan::model::index_multi(
14502 | stan::model::rvalue(obsidx, "obsidx",
14503 | stan::model::index_min_max(1,
14504 | stan::model::rvalue(Nobs, "Nobs",
14505 | stan::model::index_uni(mm)))))),
14506 | stan::model::rvalue(Sigmainv, "Sigmainv",
14507 | stan::model::index_uni(mm),
14508 | stan::model::index_min_max(1,
14509 | (stan::model::rvalue(Nobs, "Nobs",
14510 | stan::model::index_uni(mm)) + 1)),
14511 | stan::model::index_min_max(1,
14512 | (stan::model::rvalue(Nobs, "Nobs",
14513 | stan::model::index_uni(mm)) + 1))),
14514 | ((r2 - r1) + 1), pstream__));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block<const Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::colPivHouseholderQr() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]'
669 | return ColPivHouseholderQR<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t<T> stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix<double, -1, -1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<T> = double]'
27 | return m.colPivHouseholderQr().logAbsDeterminant();
| ~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:16309:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16309 | stan::math::log_determinant(
16310 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:127: required from 'static void Eigen::internal::triangular_solve_vector<LhsScalar, RhsScalar, Index, 1, Mode, Conjugate, 1>::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long long int; int Mode = 6; bool Conjugate = false]'
78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map<const Matrix<RhsScalar,Dynamic,1> >(rhs+s,k))).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: required from 'static void Eigen::internal::triangular_solver_selector<Lhs, Rhs, Side, Mode, 0, 1>::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Side = 1; int Mode = 6]'
71 | triangular_solve_vector<LhsScalar, RhsScalar, Index, Side, Mode, LhsProductTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
72 | (int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
73 | ::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs);
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
594 | _set_noalias(other);
| ~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
18 | return std::forward<T>(a);
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]'
27 | const auto& M_ref = to_ref(M);
| ~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:19: required from here
34 | return crossprod(B * llt_of_S.matrixU());
| ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int Mode = 5; bool LhsIsTriangular = true; Lhs = const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Rhs = Eigen::Matrix<double, -1, -1>; typename Dest::Scalar = double]'
462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Solve<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Solve<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, Eigen::Dense>'
86 | class SolveImpl<Decomposition,RhsType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >'
62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:644:39: required from 'static void Eigen::internal::Assignment<DstXprType, Eigen::Inverse<Eigen::ColPivHouseholderQR<MatrixType> >, Eigen::internal::assign_op<typename DstXprType::Scalar, typename Eigen::ColPivHouseholderQR<MatrixType>::Scalar>, Eigen::internal::Dense2Dense>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<typename DstXprType::Scalar, typename Eigen::ColPivHouseholderQR<MatrixType>::Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, -1>; MatrixType = Eigen::Matrix<double, -1, -1>; SrcXprType = Eigen::Inverse<Eigen::ColPivHouseholderQR<Eigen::Matrix<double, -1, -1> > >; typename DstXprType::Scalar = double; typename Eigen::ColPivHouseholderQR<MatrixType>::Scalar = double]'
644 | dst = src.nestedExpression().solve(MatrixType::Identity(src.rows(), src.cols()));
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/log_determinant.hpp:23:0: required from 'stan::math::var stan::math::log_determinant(const T&) [with T = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_rev_matrix_t<T>* <anonymous> = 0; var = var_value<double>]'
23 | auto arena_m_inv_transpose = to_arena(m_hh.inverse().transpose());
stanExports_stanmarg.h:14144:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14144 | stan::math::log_determinant(
14145 | stan::model::rvalue(Sigma, "Sigma", stan::model::index_uni(g))),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >; Functor = add_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >; Functor = Eigen::internal::add_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t<T, L, U> stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; T_dof = int; T_scale = Eigen::Matrix<var_value<double>, -1, -1>; stan::require_stan_scalar_t<T2>* <anonymous> = 0; stan::require_all_matrix_t<T_y, T_scale>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]'
92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref));
stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14327 | lp_accum__.add(stan::math::wishart_lpdf<false>(
14328 | stan::math::multiply(
14329 | (stan::model::rvalue(N, "N",
14330 | stan::model::index_uni(g)) - 1),
14331 | stan::model::rvalue(Sstar, "Sstar",
14332 | stan::model::index_uni(g))),
14333 | (stan::model::rvalue(N, "N",
14334 | stan::model::index_uni(g)) - 1),
14335 | stan::model::rvalue(Sigma, "Sigma",
14336 | stan::model::index_uni(g))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Functor = sub_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Derived = Eigen::Block<Eigen::Block<Eigen::Ref<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:305:153: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::lu() const [with Derived = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
619 | return PartialPivLU<PlainObject>(eval());
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:4181:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4181 | stan::model::assign(T2p11,
4182 | stan::math::subtract(Sig11,
4183 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4184 | stan::math::transpose(Sig12))), "assigning variable T2p11");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0> >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:4181:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4181 | stan::model::assign(T2p11,
4182 | stan::math::subtract(Sig11,
4183 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4184 | stan::math::transpose(Sig12))), "assigning variable T2p11");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, 1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:4192:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4192 | stan::model::assign(ymis,
4193 | stan::math::add(
4194 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx),
4195 | stan::model::index_multi(
4196 | stan::model::rvalue(obsidx, "obsidx",
4197 | stan::model::index_min_max(
4198 | (stan::model::rvalue(Nobs, "Nobs",
4199 | stan::model::index_uni(mm)) + 1), p)))),
4200 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4201 | stan::math::subtract(
4202 | stan::model::rvalue(YXstar, "YXstar",
4203 | stan::model::index_uni(jj),
4204 | stan::model::index_min_max(1,
4205 | stan::model::rvalue(Nobs, "Nobs",
4206 | stan::model::index_uni(mm)))),
4207 | stan::model::rvalue(Mu, "Mu",
4208 | stan::model::index_uni(grpidx),
4209 | stan::model::index_multi(
4210 | stan::model::rvalue(obsidx, "obsidx",
4211 | stan::model::index_min_max(1,
4212 | stan::model::rvalue(Nobs, "Nobs",
4213 | stan::model::index_uni(mm))))))))),
4214 | "assigning variable ymis");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Product<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >, 1> >; Functor = Eigen::internal::assign_op<double, double>; int Version = 1; Eigen::Index = long long int]'
654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; stan::require_eigen_t<T_desired>* <anonymous> = 0]'
21 | return tcrossprod(M.transpose());
| ~~~~~~~~~~^~~~~~~~~~~~~~~
stanExports_stanmarg.h:4245:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4245 | stan::math::crossprod(
4246 | stan::model::rvalue(YXfull, "YXfull",
4247 | stan::model::index_min_max(r1, r2), stan::model::index_omni())),
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Dense>'
372 | typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::Flags>::type type;
| ^~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Matrix<double, -1, -1>, Eigen::DenseShape, Eigen::DenseShape, 7>'
369 | typedef typename nested_eval<Lhs,1>::type LhsNested;
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Matrix<double, -1, -1>; Scalar = double]'
485 | return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha);
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Matrix<double, -1, -1>]'
445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1));
| ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >'
1043 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:32: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:48: required from 'static void Eigen::internal::triangular_product_impl<Mode, false, Lhs, true, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>; int Mode = 5; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >; Rhs = const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; typename Dest::Scalar = double]'
194 | ::run(rhs.transpose(),lhs.transpose(), dstT, alpha);
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~~~
40 | .solve(Eigen::Matrix<T_return, Eigen::Dynamic, Eigen::Dynamic>(b)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
41 | .transpose())
| ~~~~~~~~~~~~~
42 | .transpose();
| ~~~~~~~~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~~~
40 | .solve(Eigen::Matrix<T_return, Eigen::Dynamic, Eigen::Dynamic>(b)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
41 | .transpose())
| ~~~~~~~~~~~~~
42 | .transpose();
| ~~~~~~~~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:54: required from 'static void Eigen::internal::trmv_selector<Mode, 1>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]'
341 | dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; typename Dest::Scalar = double]'
457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; typename Dest::Scalar = double]'
462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer<T>::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, std::allocator<Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value<double>; Sizes = {int}; stan::require_std_vector_t<Ret>* <anonymous> = 0; T = stan::math::var_value<double>; size_t = long long unsigned int]'
979 | this->read_constrain_corr_matrix<value_type_t<Ret>, Jacobian>(
980 | lp, sizes...));
stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix<
12985 | std::vector<Eigen::Matrix<local_scalar_t__,-1,-1>>,
12986 | jacobian__>(lp__, Psi_r_mat_1_1dim__,
12987 | Psi_r_mat_1_3dim__);
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >; Functor = Eigen::internal::assign_op<double, double>; int Version = 1; Eigen::Index = long long int]'
654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<stan::math::var_value<double>, -1, -1>; T4__ = stan::math::var_value<double>; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = stan::math::var_value<double>; typename stan::base_type<T>::type = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14152 | sig_inv_update(
14153 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
14154 | stan::model::index_uni(
14155 | stan::model::rvalue(grpnum, "grpnum",
14156 | stan::model::index_uni(patt)))),
14157 | stan::model::rvalue(Obsvar, "Obsvar",
14158 | stan::model::index_uni(patt), stan::model::index_omni()),
14159 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
14160 | (p + q),
14161 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
14162 | stan::model::index_uni(
14163 | stan::model::rvalue(grpnum, "grpnum",
14164 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, -1>; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Matrix<double, -1, -1>; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> > >'
357 | class redux_evaluator : public internal::evaluator<_XprType>
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<stan::model::rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
414 | ThisEvaluator thisEval(derived());
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, 1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::CwiseNullaryOp<rvalue<const Eigen::Matrix<double, -1, 1>&>(const Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0> >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:4192:0: required from 'std::vector<Eigen::Matrix<typename boost::math::tools::promote_args<RT1, RT2, A>::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<RhsScalar, -1, 1> >&, const std::vector<Eigen::Matrix<LhsScalar, -1, -1, 0> >&, const std::vector<int>&, const std::vector<std::vector<int> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_stan_scalar<T3__> >* <anonymous> = 0; typename boost::math::tools::promote_args<RT1, RT2, A>::type = double; std::ostream = std::basic_ostream<char>]'
4192 | stan::model::assign(ymis,
4193 | stan::math::add(
4194 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx),
4195 | stan::model::index_multi(
4196 | stan::model::rvalue(obsidx, "obsidx",
4197 | stan::model::index_min_max(
4198 | (stan::model::rvalue(Nobs, "Nobs",
4199 | stan::model::index_uni(mm)) + 1), p)))),
4200 | stan::math::multiply(stan::math::multiply(Sig12, S22inv),
4201 | stan::math::subtract(
4202 | stan::model::rvalue(YXstar, "YXstar",
4203 | stan::model::index_uni(jj),
4204 | stan::model::index_min_max(1,
4205 | stan::model::rvalue(Nobs, "Nobs",
4206 | stan::model::index_uni(mm)))),
4207 | stan::model::rvalue(Mu, "Mu",
4208 | stan::model::index_uni(grpidx),
4209 | stan::model::index_multi(
4210 | stan::model::rvalue(obsidx, "obsidx",
4211 | stan::model::index_min_max(1,
4212 | stan::model::rvalue(Nobs, "Nobs",
4213 | stan::model::index_uni(mm))))))))),
4214 | "assigning variable ymis");
stanExports_stanmarg.h:17860:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
17860 | estep(YXstar, Mu_sat, Sigma_sat, Nobs, Obsvar, startrow,
17861 | endrow, grpnum, Np, Ng, pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:59: required from 'static void Eigen::internal::gemv_dense_selector<2, 1, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; typename Dest::Scalar = double]'
379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from 'static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>; Rhs = Eigen::Matrix<double, -1, -1>; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; int StorageOrder = 0; bool BlasCompatible = true; typename Dest::Scalar = double]'
207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> >, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:106: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:77: required from 'static void Eigen::internal::triangular_matrix_vector_product<Index, Mode, LhsScalar, ConjLhs, RhsScalar, ConjRhs, 1, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]'
137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Matrix<double, 8, 8, 1, 8, 8> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Matrix<double, 8, 8, 1, 8, 8> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase<Eigen::Matrix<double, 8, 8, 1, 8, 8> >'
98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>'
63 | template<typename MatrixType, int _DiagIndex> class Diagonal
| ^~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Matrix<double, -1, -1>; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Matrix<double, -1, -1>; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase<Derived>::EvalReturnType Eigen::DenseBase<Derived>::eval() const [with Derived = Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>; EvalReturnType = const Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
412 | return typename internal::eval<Derived>::type(derived());
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t<T> stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_not_eigen_col_vector_t<EigMat2>* <anonymous> = 0; stan::require_vt_same<T_U, T_CPCs>* <anonymous> = 0; stan::require_all_vt_arithmetic<EigMat1, EigMat2>* <anonymous> = 0; stan::plain_type_t<T> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]'
37 | (B_ref.transpose() * A_ref * B_ref).eval());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
stanExports_stanmarg.h:15786:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15786 | stan::math::quad_form_sym(
15787 | stan::model::rvalue(Psi, "Psi", stan::model::index_uni(g)),
15788 | stan::math::transpose(
15789 | stan::model::rvalue(Lambda_y_A, "Lambda_y_A",
15790 | stan::model::index_uni(g))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; SrcXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; Functor = swap_assign_op<double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; SrcXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; Functor = Eigen::internal::swap_assign_op<double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; Src = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; Func = swap_assign_op<double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; Src = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; Func = swap_assign_op<double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:424:22: required from 'void Eigen::DenseBase<Derived>::swap(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>; Derived = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>]'
424 | call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:1129:51: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t<T1, T2> stan::math::trace_inv_quad_form_ldlt(LDLT_factor<T>&, const EigMat2&) [with T = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; <template-parameter-1-3> = void; stan::return_type_t<T1, T2> = double]'
36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum();
| ~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; T_covar = Eigen::Matrix<double, -1, -1>; stan::return_type_t<T, L, U> = double]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:18523:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18523 | stan::math::multi_normal_lpdf<false>(
18524 | stan::model::rvalue(YXstar, "YXstar",
18525 | stan::model::index_uni(jj),
18526 | stan::model::index_multi(
18527 | stan::model::rvalue(xdatidx, "xdatidx",
18528 | stan::model::index_min_max(1,
18529 | stan::model::rvalue(Nx, "Nx",
18530 | stan::model::index_uni(mm)))))),
18531 | stan::model::rvalue(Mu, "Mu",
18532 | stan::model::index_uni(grpidx),
18533 | stan::model::index_multi(
18534 | stan::model::rvalue(xidx, "xidx",
18535 | stan::model::index_min_max(1,
18536 | stan::model::rvalue(Nx, "Nx",
18537 | stan::model::index_uni(mm)))))),
18538 | stan::model::rvalue(Sigma, "Sigma",
18539 | stan::model::index_uni(grpidx),
18540 | stan::model::index_multi(
18541 | stan::model::rvalue(xidx, "xidx",
18542 | stan::model::index_min_max(1,
18543 | stan::model::rvalue(Nx, "Nx",
18544 | stan::model::index_uni(mm))))),
18545 | stan::model::index_multi(
18546 | stan::model::rvalue(xidx, "xidx",
18547 | stan::model::index_min_max(1,
18548 | stan::model::rvalue(Nx, "Nx",
18549 | stan::model::index_uni(mm))))))))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 1, 8, 8> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 1, 8, 8> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 1, 8, 8> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 1, 8, 8> >'
60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, 8, 8, 1, 8, 8>; Scalar = double]'
347 | return derived() = Constant(rows(), cols(), val);
| ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase<Derived>::setZero() [with Derived = Eigen::Matrix<double, 8, 8, 1, 8, 8>]'
548 | return setConstant(Scalar(0));
| ^~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 2; bool LhsIsTriangular = true; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Matrix<double, -1, -1>; typename Dest::Scalar = double]'
462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true>, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true, true>'
329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; Rhs = Eigen::Matrix<double, -1, -1>; typename Dest::Scalar = double]'
462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; SrcXprType = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Functor = swap_assign_op<double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; SrcXprType = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Functor = Eigen::internal::swap_assign_op<double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Src = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Func = swap_assign_op<double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Src = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Func = swap_assign_op<double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:424:22: required from 'void Eigen::DenseBase<Derived>::swap(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Derived = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>]'
424 | call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:1129:51: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t<T, L, U> stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector<Eigen::Matrix<var_value<double>, -1, 1>, std::allocator<Eigen::Matrix<var_value<double>, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:767&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; T_covar = Eigen::Matrix<var_value<double>, -1, -1>; stan::return_type_t<T, L, U> = var_value<double>]'
98 | sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_col - mu_col);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t<T2> model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
14424 | lp_accum__.add(stan::math::multi_normal_lpdf<false>(
14425 | stan::model::rvalue(YXstar, "YXstar",
14426 | stan::model::index_min_max(r1, r2),
14427 | stan::model::index_min_max(1,
14428 | stan::model::rvalue(Nobs, "Nobs",
14429 | stan::model::index_uni(mm)))),
14430 | stan::model::rvalue(Mu, "Mu",
14431 | stan::model::index_uni(grpidx),
14432 | stan::model::index_multi(
14433 | stan::model::rvalue(obsidx, "obsidx",
14434 | stan::model::index_min_max(1,
14435 | stan::model::rvalue(Nobs, "Nobs",
14436 | stan::model::index_uni(mm)))))),
14437 | stan::model::rvalue(Sigma, "Sigma",
14438 | stan::model::index_uni(grpidx),
14439 | stan::model::index_multi(
14440 | stan::model::rvalue(obsidx, "obsidx",
14441 | stan::model::index_min_max(1,
14442 | stan::model::rvalue(Nobs, "Nobs",
14443 | stan::model::index_uni(mm))))),
14444 | stan::model::index_multi(
14445 | stan::model::rvalue(obsidx, "obsidx",
14446 | stan::model::index_min_max(1,
14447 | stan::model::rvalue(Nobs, "Nobs",
14448 | stan::model::index_uni(mm))))))));
stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]'
22491 | return log_prob_impl<propto__, jacobian__>(params_r, params_i, pstream);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream<char>]'
40 | var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
41 | ad_params_r, params_i, msgs);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1183 | lp = stan::model::log_prob_grad<true,true>(model_, par_r, par_i, gradient, &rstan::io::rcout);
stanExports_stanmarg.cc:23:0: required from here
23 | .method("grad_log_prob", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::grad_log_prob)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; SrcXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Functor = swap_assign_op<double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; SrcXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Functor = Eigen::internal::swap_assign_op<double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Src = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Func = swap_assign_op<double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Src = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Func = swap_assign_op<double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:424:22: required from 'void Eigen::DenseBase<Derived>::swap(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>]'
424 | call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:1033:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~~~
40 | .solve(Eigen::Matrix<T_return, Eigen::Dynamic, Eigen::Dynamic>(b)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
41 | .transpose())
| ~~~~~~~~~~~~~
42 | .transpose();
| ~~~~~~~~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, -1>; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Matrix<double, -1, -1>; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 1> >; Functor = Eigen::internal::sub_assign_op<double, double>; int Version = 1; Eigen::Index = long long int]'
654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:442:0: required from 'void stan::model::assign(Mat1&&, Mat2&&, const char*, index_min_max, index_min_max) [with Mat1 = Eigen::Matrix<double, -1, -1>&; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> >; stan::require_dense_dynamic_t<T_y>* <anonymous> = 0]'
442 | internal::assign_impl(
443 | x.block(row_idx.min_ - 1, col_idx.min_ - 1, row_size, col_size), y,
444 | name);
stanExports_stanmarg.h:4435:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector<int>&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix<double, -1, -1>; T4__ = double; stan::require_all_t<stan::is_eigen_matrix_dynamic<T>, stan::is_vt_not_complex<T0__>, stan::is_stan_scalar<T_a> >* <anonymous> = 0; typename boost::math::tools::promote_args<typename stan::base_type<T, void>::type, T1__>::type = double; typename stan::base_type<T>::type = double; std::ostream = std::basic_ostream<char>]'
4435 | stan::model::assign(out,
4436 | stan::math::subtract(
4437 | stan::model::rvalue(Sigmainv, "Sigmainv",
4438 | stan::model::index_multi(
4439 | stan::model::rvalue(obsidx, "obsidx",
4440 | stan::model::index_min_max(1, Nobs))),
4441 | stan::model::index_multi(
4442 | stan::model::rvalue(obsidx, "obsidx",
4443 | stan::model::index_min_max(1, Nobs)))),
4444 | stan::math::multiply(stan::math::transpose(A),
4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out",
4446 | stan::model::index_min_max(1, Nobs),
4447 | stan::model::index_min_max(1, Nobs));
stanExports_stanmarg.h:16317:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
16317 | sig_inv_update(
16318 | stan::model::rvalue(Sigmainv_grp, "Sigmainv_grp",
16319 | stan::model::index_uni(
16320 | stan::model::rvalue(grpnum, "grpnum",
16321 | stan::model::index_uni(patt)))),
16322 | stan::model::rvalue(Obsvar, "Obsvar",
16323 | stan::model::index_uni(patt), stan::model::index_omni()),
16324 | stan::model::rvalue(Nobs, "Nobs", stan::model::index_uni(patt)),
16325 | (p + q),
16326 | stan::model::rvalue(logdetSigma_grp, "logdetSigma_grp",
16327 | stan::model::index_uni(
16328 | stan::model::rvalue(grpnum, "grpnum",
16329 | stan::model::index_uni(patt)))), pstream__),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Matrix<double, -1, -1>; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Matrix<double, -1, -1>; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:114: required from 'static void Eigen::internal::triangular_matrix_vector_product<Index, Mode, LhsScalar, ConjLhs, RhsScalar, ConjRhs, 1, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]'
137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: required from 'static void Eigen::internal::trmv_selector<Mode, 1>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]'
327 | internal::triangular_matrix_vector_product
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
328 | <Index,Mode,
| ~~~~~~~~~~~~
329 | LhsScalar, LhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
330 | RhsScalar, RhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
331 | RowMajor>
| ~~~~~~~~~
332 | ::run(actualLhs.rows(),actualLhs.cols(),
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
333 | actualLhs.data(),actualLhs.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
334 | actualRhsPtr,1,
| ~~~~~~~~~~~~~~~
335 | dest.data(),dest.innerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
336 | actualAlpha);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >'
1043 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 37 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 35 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op<double, double>]'
780 | DstEvaluatorType dstEvaluator(dst);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Derived = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:27: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; SrcXprType = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false>; Functor = assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; SrcXprType = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false>; Functor = Eigen::internal::assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Src = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false>; Func = assign_op<double, double>]'
890 | Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Src = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false>; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
858 | call_assignment_no_alias(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, false>; Src = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, false>]'
836 | call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
423 | : Base(other.derived())
| ^
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix<typename stan::return_type<T1, T2>::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix<double, -1, -1>; EigMat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, -1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_vt_fvar<EigMat1, EigMat2>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]'
36 | return Eigen::Matrix<T_return, EigMat2::RowsAtCompileTime,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
37 | EigMat2::ColsAtCompileTime>(A)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
38 | .transpose()
| ~~~~~~~~~~~~
39 | .lu()
| ~~~~~
40 | .solve(Eigen::Matrix<T_return, Eigen::Dynamic, Eigen::Dynamic>(b)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
41 | .transpose())
| ~~~~~~~~~~~~~
42 | .transpose();
| ~~~~~~~~~~^~
stanExports_stanmarg.h:15736:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
15736 | stan::math::mdivide_right(
15737 | stan::model::rvalue(Lambda_y, "Lambda_y",
15738 | stan::model::index_uni(g)),
15739 | stan::math::subtract(I,
15740 | stan::model::rvalue(B, "B", stan::model::index_uni(g)))),
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; Rhs = Eigen::Matrix<double, -1, -1>; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Matrix<double, -1, -1>; CoeffReturnType = double; Eigen::Index = long long int]'
606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, Eigen::Matrix<double, -1, -1>, 1> >; Functor = Eigen::internal::assign_op<double, double>; int Version = 1; Eigen::Index = long long int]'
654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
| ~~~~~~~~~~~^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix<double, -1, -1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, -1> >, const Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]'
60 | internal::assign_impl(x, std::forward<U>(y), name);
stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix<typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector<Eigen::Matrix<Type, -1, 1> >&, const std::vector<Eigen::Matrix<Scalar, -1, -1> >&, const T2__&, const std::vector<Eigen::Matrix<T_job_param, -1, 1> >&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const std::vector<int>&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const std::vector<int>&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix<double, -1, -1>; T3__ = double; T9__ = Eigen::Matrix<double, -1, 1>; T10__ = Eigen::Matrix<double, -1, -1>; T11__ = Eigen::Matrix<double, -1, 1>; T12__ = Eigen::Matrix<double, -1, -1>; stan::require_all_t<stan::is_stan_scalar<Var1>, stan::is_stan_scalar<T_a>, stan::is_eigen_matrix_dynamic<T2__>, stan::is_vt_not_complex<T2__>, stan::is_stan_scalar<T3__>, stan::is_col_vector<T9__>, stan::is_vt_not_complex<T9__>, stan::is_eigen_matrix_dynamic<T10__>, stan::is_vt_not_complex<T10__>, stan::is_col_vector<T11__>, stan::is_vt_not_complex<T11__>, stan::is_eigen_matrix_dynamic<T12__>, stan::is_vt_not_complex<T12__> >* <anonymous> = 0; typename boost::math::tools::promote_args<T0__, T1__, typename stan::base_type<T2__, void>::type, T3__, typename stan::base_type<T9__, void>::type, typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type>::type = double; typename stan::base_type<T2__, void>::type = double; typename stan::base_type<T9__, void>::type = double; typename boost::math::tools::promote_args<typename stan::base_type<T10__, void>::type, typename stan::base_type<T11__, void>::type, typename stan::base_type<T12__, void>::type>::type = double; typename stan::base_type<T10__, void>::type = double; typename stan::base_type<T11__, void>::type = double; typename stan::base_type<T12__, void>::type = double; std::ostream = std::basic_ostream<char>]'
3413 | stan::model::assign(Vinv_11,
3414 | stan::math::add(Sigma_zz_inv,
3415 | stan::math::multiply(nj,
3416 | stan::math::multiply(stan::math::transpose(Sigma_yz_zi),
3417 | Sigma_ji_yz_zi))), "assigning variable Vinv_11");
stanExports_stanmarg.h:18174:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]'
18174 | twolevel_logdens(
18175 | stan::model::rvalue(mean_d_full, "mean_d_full",
18176 | stan::model::index_min_max(r1, r2)),
18177 | stan::model::rvalue(cov_d_full, "cov_d_full",
18178 | stan::model::index_min_max(r1, r2)),
18179 | stan::model::rvalue(S_PW, "S_PW",
18180 | stan::model::index_uni(grpidx)),
18181 | stan::model::rvalue(YX, "YX",
18182 | stan::model::index_min_max(r3, r4)),
18183 | stan::model::rvalue(nclus, "nclus",
18184 | stan::model::index_uni(grpidx), stan::model::index_omni()),
18185 | stan::model::rvalue(cluster_size, "cluster_size",
18186 | stan::model::index_min_max(r1, r2)),
18187 | stan::model::rvalue(cluster_size, "cluster_size",
18188 | stan::model::index_min_max(r1, r2)),
18189 | stan::model::rvalue(nclus, "nclus",
18190 | stan::model::index_uni(grpidx), stan::model::index_uni(2)),
18191 | stan::model::rvalue(intone, "intone",
18192 | stan::model::index_min_max(1,
18193 | stan::model::rvalue(nclus, "nclus",
18194 | stan::model::index_uni(grpidx),
18195 | stan::model::index_uni(2)))),
18196 | stan::model::rvalue(Mu, "Mu", stan::model::index_uni(grpidx)),
18197 | stan::model::rvalue(Sigma, "Sigma",
18198 | stan::model::index_uni(grpidx)),
18199 | stan::model::rvalue(Mu_c, "Mu_c",
18200 | stan::model::index_uni(grpidx)),
18201 | stan::model::rvalue(Sigma_c, "Sigma_c",
18202 | stan::model::index_uni(grpidx)), ov_idx1, ov_idx2,
18203 | within_idx, between_idx, both_idx, p_tilde, N_within,
18204 | N_between, N_both, pstream__), "assigning variable log_lik",
stanExports_stanmarg.h:22480:0: required from 'void model_stanmarg_namespace::model_stanmarg::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]'
22480 | write_array_impl(base_rng, params_r, params_i, vars,
22481 | emit_transformed_parameters, emit_generated_quantities, pstream);
D:/RCompile/CRANpkg/lib/4.6/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]'
1105 | model_.write_array(base_rng, params_r, params_i, par);
stanExports_stanmarg.cc:26:0: required from here
26 | .method("constrain_pars", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::constrain_pars)
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> > >'
722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from 'void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >; Functor = sub_assign_op<double, double>]'
774 | SrcEvaluatorType srcEvaluator(src);
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; Weak = void]'
954 | call_dense_assignment_loop(dst, src, func);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
238 | return Base::operator=(other);
| ~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate())
| ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
454 | .setLength(mat.rows() - 1)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~
455 | .setShift(1);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]'
434 | tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]'
181 | compute(matrix.derived(), options);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here
19 | Eigen::SelfAdjointEigenSolver<matrix_d> solver(H);
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from 'void stan::math::internal::callback_vari<T, F>::chain() [with T = double; F = stan::math::sum<arena_allocator<var_value<double> > >(const std::vector<var_value<double>, arena_allocator<var_value<double> > >&)::<lambda(auto:510&)>]'
21 | inline void chain() final { rev_functor_(*this); }
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> > >'
39 | template<typename Derived> class ArrayBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >'
42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from 'void stan::math::internal::callback_vari<T, F>::chain() [with T = double; F = stan::math::trace<Eigen::Matrix<var_value<double>, -1, -1> >(const Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(const auto:711&)>]'
21 | inline void chain() final { rev_functor_(*this); }
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, 8>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari<R1, C1, R2, C2>::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]'
66 | -= adjB * alloc_->C_.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here
62 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1>, Eigen::Dense>'
103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1> >'
58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
| ^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:89:0: required from 'void stan::math::internal::quad_form_vari<Ta, Ra, Ca, Tb, Rb, Cb>::chain() [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
89 | matrix_d adjC = impl_->C_.adj();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here
88 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::Matrix<var_value<double>, -1, -1>&>(Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::Matrix<var_value<double>, -1, -1>&>(Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::Matrix<var_value<double>, -1, -1>&>(Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl<stan::math::value_of<Eigen::Matrix<var_value<double>, -1, -1>&>(Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1>, Eigen::Dense>'
94 | class CwiseUnaryOpImpl
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::Matrix<var_value<double>, -1, -1>&>(Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>::<lambda(const auto:12&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, -1> >'
55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
| ^~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of<Eigen::Matrix<var_value<double>, -1, -1>&>(Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)> [with auto:11 = Eigen::Matrix<stan::math::var_value<double>, -1, -1>]'
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of<Eigen::Matrix<var_value<double>, -1, -1>&>(Eigen::Matrix<var_value<double>, -1, -1>&)::<lambda(auto:11&)>; Args = {Eigen::Matrix<stan::math::var_value<double, void>, -1, -1, 0, -1, -1>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]'
370 | decltype(std::declval<F>()(std::declval<Args&>()...))>* = nullptr>
| ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from 'auto stan::math::value_of(EigMat&&) [with EigMat = Eigen::Matrix<var_value<double>, -1, -1>&; stan::require_eigen_dense_base_t<EigMat>* <anonymous> = 0; stan::require_not_st_arithmetic<T>* <anonymous> = 0]'
73 | return make_holder(
| ~~~~~~~~~~~^
74 | [](auto& a) {
| ~~~~~~~~~~~~~
75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); });
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
76 | },
| ~~
77 | std::forward<EigMat>(M));
| ~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from 'void stan::math::internal::quad_form_vari<Ta, Ra, Ca, Tb, Rb, Cb>::chain() [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here
88 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, const Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, const Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, const Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, const Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, const Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from 'void stan::math::internal::quad_form_vari<Ta, Ra, Ca, Tb, Rb, Cb>::chainB(Eigen::Matrix<stan::math::var_value<double>, Rb, Cb>&, const Eigen::Matrix<double, R1, C1>&, const Eigen::Matrix<double, Rb, Cb>&, const Eigen::Matrix<double, Cb, Cb>&) [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from 'void stan::math::internal::quad_form_vari<Ta, Ra, Ca, Tb, Rb, Cb>::chainAB(Eigen::Matrix<T, R, C>&, Eigen::Matrix<Tb, Rb, Cb>&, const Eigen::Matrix<double, R1, C1>&, const Eigen::Matrix<double, Rb, Cb>&, const Eigen::Matrix<double, Cb, Cb>&) [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
78 | chainB(B, Ad, Bd, adjC);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from 'void stan::math::internal::quad_form_vari<Ta, Ra, Ca, Tb, Rb, Cb>::chain() [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here
88 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from 'static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Matrix<double, -1, 1>; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; bool NeedToTranspose = false; ResScalar = double]'
37 | return a.template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from 'double stan::mcmc::diag_e_metric<Model, BaseRNG>::T(stan::mcmc::diag_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here
20 | double T(diag_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:39: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from 'static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Matrix<double, -1, 1>; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; bool NeedToTranspose = false; ResScalar = double]'
37 | return a.template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from 'double stan::mcmc::diag_e_metric<Model, BaseRNG>::T(stan::mcmc::diag_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p));
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here
20 | double T(diag_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase<Derived>::_init1(const Eigen::DenseBase<ElseDerived>&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
883 | this->_set_noalias(other);
| ~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
332 | Base::template _init1<T>(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Func = sub_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
850 | typename plain_matrix_type<Src>::type tmp(src);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Derived = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari<R1, C1, R2, C2>::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]'
65 | Eigen::Map<matrix_vi>(variRefA_, M_, M_).adj()
66 | -= adjB * alloc_->C_.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here
62 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, 7>'
120 | class dense_product_base
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>'
152 | class ProductImpl<Lhs,Rhs,Option,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>'
71 | class Product : public ProductImpl<_Lhs,_Rhs,Option,
| ^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase<Derived>::_init1(const Eigen::DenseBase<ElseDerived>&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
883 | this->_set_noalias(other);
| ~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
332 | Base::template _init1<T>(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Func = sub_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
850 | typename plain_matrix_type<Src>::type tmp(src);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Derived = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari<R1, C1, R2, C2>::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]'
65 | Eigen::Map<matrix_vi>(variRefA_, M_, M_).adj()
66 | -= adjB * alloc_->C_.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here
62 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase<Derived>::_init1(const Eigen::DenseBase<ElseDerived>&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
883 | this->_set_noalias(other);
| ~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
332 | Base::template _init1<T>(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Func = sub_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
850 | typename plain_matrix_type<Src>::type tmp(src);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Derived = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari<R1, C1, R2, C2>::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]'
65 | Eigen::Map<matrix_vi>(variRefA_, M_, M_).adj()
66 | -= adjB * alloc_->C_.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here
62 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase<Derived>::_init1(const Eigen::DenseBase<ElseDerived>&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]'
883 | this->_set_noalias(other);
| ~~~~~~~~~~~~~~~~~~^~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]'
332 | Base::template _init1<T>(x);
| ~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Func = sub_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
850 | typename plain_matrix_type<Src>::type tmp(src);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>; Derived = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >]'
164 | call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari<R1, C1, R2, C2>::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]'
65 | Eigen::Map<matrix_vi>(variRefA_, M_, M_).adj()
66 | -= adjB * alloc_->C_.transpose();
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here
62 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, -1, 1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, -1, 1, true>, 1>'
302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, -1, 1, true>, 3>'
555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, -1, 1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, -1, 1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, -1, 1, true>, 0>'
37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1> >; Src = Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, const Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0> >; Func = add_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]'
850 | typename plain_matrix_type<Src>::type tmp(src);
| ^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 0>, const Eigen::Product<Eigen::Product<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, -1>, 0> >; Derived = Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, -1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, -1> >]'
177 | call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from 'void stan::math::internal::quad_form_vari<Ta, Ra, Ca, Tb, Rb, Cb>::chainB(Eigen::Matrix<stan::math::var_value<double>, Rb, Cb>&, const Eigen::Matrix<double, R1, C1>&, const Eigen::Matrix<double, Rb, Cb>&, const Eigen::Matrix<double, Cb, Cb>&) [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from 'void stan::math::internal::quad_form_vari<Ta, Ra, Ca, Tb, Rb, Cb>::chainAB(Eigen::Matrix<T, R, C>&, Eigen::Matrix<Tb, Rb, Cb>&, const Eigen::Matrix<double, R1, C1>&, const Eigen::Matrix<double, Rb, Cb>&, const Eigen::Matrix<double, Cb, Cb>&) [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
78 | chainB(B, Ad, Bd, adjC);
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from 'void stan::math::internal::quad_form_vari<Ta, Ra, Ca, Tb, Rb, Cb>::chain() [with Ta = stan::math::var_value<double>; int Ra = -1; int Ca = -1; Tb = stan::math::var_value<double>; int Rb = -1; int Cb = -1]'
91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_),
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here
88 | virtual void chain() {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true, false>'
172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
| ^~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true, Eigen::Dense>'
154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>'
103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
| ^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from 'static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >; Rhs = Eigen::Matrix<double, -1, -1>; Dest = Eigen::Matrix<double, 1, -1>; int StorageOrder = 0; bool BlasCompatible = true; typename Dest::Scalar = double]'
207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
| ~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>'
148 | class CwiseBinaryOpImpl
| ^~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >'
77 | class CwiseBinaryOp :
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >, 0>':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >, 2>'
481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > > >'
41 | template<typename Derived> class DenseBase
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > > >'
48 | template<typename Derived> class MatrixBase
| ^~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>'
118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >'
52 | template<typename MatrixType> class Transpose
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
56 | >::type PacketReturnType;
| ^~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>'
311 | CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> > >'
90 | struct evaluator : public unary_evaluator<T>
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> > >'
100 | struct evaluator<const T>
| ^~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>'
739 | CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
| ^~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
1071 | PacketAlignment = unpacket_traits<PacketScalar>::alignment,
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Eigen::Index = long long int]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >; Scalar = double]'
243 | const Index alignedStart = internal::first_default_aligned(xpr);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
418 | return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]'
463 | return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
| ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]'
50 | return a.transpose().template binaryExpr<conj_prod>(b).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]'
84 | return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]'
251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
124 | generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]'
35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
| ^
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]'
137 | return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]'
22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p;
D:/RCompile/CRANpkg/lib/4.6/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here
21 | double T(dense_e_point& z) {
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<double>::type' {aka '__m128d'} [-Wignored-attributes]
654 | return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
| ^~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h: In function 'static void Eigen::internal::selfadjoint_product_impl<Lhs, LhsMode, false, Rhs, 0, true>::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: warning: 'result' may be used uninitialized [-Wmaybe-uninitialized]
227 | internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
229 | (
| ^
230 | lhs.rows(), // size
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
232 | actualRhsPtr, // rhs info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
233 | actualDestPtr, // result info
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
234 | actualAlpha // scale factor
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
235 | );
| ~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:41:6: note: by argument 4 of type 'const double*' to 'static void Eigen::internal::selfadjoint_matrix_vector_product<Scalar, Index, StorageOrder, UpLo, ConjugateLhs, ConjugateRhs, Version>::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]' declared here
41 | void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Version>::run(
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In file included from D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/Core:341:
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h: In function 'static void Eigen::internal::trmv_selector<Mode, 1>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; int Mode = 6]':
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: warning: 'result' may be used uninitialized [-Wmaybe-uninitialized]
327 | internal::triangular_matrix_vector_product
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
328 | <Index,Mode,
| ~~~~~~~~~~~~
329 | LhsScalar, LhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
330 | RhsScalar, RhsBlasTraits::NeedToConjugate,
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
331 | RowMajor>
| ~~~~~~~~~
332 | ::run(actualLhs.rows(),actualLhs.cols(),
| ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
333 | actualLhs.data(),actualLhs.outerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
334 | actualRhsPtr,1,
| ~~~~~~~~~~~~~~~
335 | dest.data(),dest.innerStride(),
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
336 | actualAlpha);
| ~~~~~~~~~~~~
D:/RCompile/CRANpkg/lib/4.6/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:105:24: note: by argument 5 of type 'const double*' to 'static void Eigen::internal::triangular_matrix_vector_product<Index, Mode, LhsScalar, ConjLhs, RhsScalar, ConjRhs, 1, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0]' declared here
105 | EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor,Version>
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
g++ -shared -s -static-libgcc -o blavaan.dll tmp.def RcppExports.o stanExports_stanmarg.o -LD:/RCompile/CRANpkg/lib/4.6/RcppParallel/libs/x64 -lRcppParallel -LD:/RCompile/CRANpkg/lib/4.6/RcppParallel/lib/x64 -ltbb -ltbbmalloc -LD:/RCompile/CRANpkg/lib/4.6/RcppParallel/lib/x64 -Wl,-rpath,D:/RCompile/CRANpkg/lib/4.6/RcppParallel/lib/x64 -ltbb -ltbbmalloc -Ld:/rtools45/x86_64-w64-mingw32.static.posix/lib/x64 -Ld:/rtools45/x86_64-w64-mingw32.static.posix/lib -LD:/RCompile/recent/R/bin/x64 -lR
make[1]: Leaving directory '/d/temp/2025_07_01_01_50_01_1069/RtmpCWsvVz/R.INSTALL416c733c1086/blavaan/src'
make[1]: Entering directory '/d/temp/2025_07_01_01_50_01_1069/RtmpCWsvVz/R.INSTALL416c733c1086/blavaan/src'
make[1]: Leaving directory '/d/temp/2025_07_01_01_50_01_1069/RtmpCWsvVz/R.INSTALL416c733c1086/blavaan/src'
installing to d:/Rcompile/CRANpkg/lib/4.6/00LOCK-blavaan/00new/blavaan/libs/x64
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* MD5 sums
packaged installation of 'blavaan' as blavaan_0.5-8.zip
* DONE (blavaan)